Annies M (2009) Full-text prior art and chemical structure searching in e-journals and on the internet—a patent information professional’s perspective. World Pat Inf 31(4):278–284
CAS
Google Scholar
Frey J (2006) Using InChI. Chem Int 28(6):14–15
Google Scholar
Heller SR, McNaught AD (2009) The IUPAC international chemical identifier (InChI). Chem Int 31(1):7–9
CAS
Google Scholar
Heller S, McNaught A, Stein S, Tchekhovskoi D, Pletnev I (2013) InChI—the worldwide chemical structure identifier standard. J Cheminformatics 5:7
CAS
Google Scholar
Rossler U (2012) Storage of structural formulas as text. Nachr Chem 60(2):140–142
CAS
Google Scholar
Williams AJ (2012) InChI: connecting and navigating chemistry. J Cheminformatics 4:33
CAS
Google Scholar
Yerin A, McNaught A, Heller S (2013) Current status and future development in relation to IUPAC activities. Chem Int 35(6):12–15
CAS
Google Scholar
McNaught A (2006) The IUPAC chemical identifier. Chem Int 28(6):12–14
CAS
Google Scholar
Heller S, McNaught A, Pletnev I, Stein S, Tchekhovskoi D (2015) InChI, the IUPAC international chemical identifier. J Cheminformatics 7(1):23
Bachrach SM (2012) InChI: a user’s perspective. J Cheminformatics 4:34
CAS
Google Scholar
Warr WA (2011) Representation of chemical structures. Wiley Interdiscip Rev Comput Mol Sci 1(4):557–579
CAS
Google Scholar
McKay BD (1981) Practical graph isomorphism. Congr Numeratium 30:45–87
Google Scholar
Morgan HL (1965) The generation of a unique machine description for chemical structures—a technique developed at chemical abstracts service. J Chem Doc 5(2):107–113
CAS
Google Scholar
Southan C (2013) InChI in the wild: an assessment of InChIKey searching in Google. J Cheminformatics 5:10
CAS
Google Scholar
Pletnev I, Erin A, McNaught A, Blinov K, Tchekhovskoi D, Heller S (2012) InChIKey collision resistance: an experimental testing. J Cheminformatics 4:39
CAS
Google Scholar
Grethe G, Goodman J, Allen C (2013) International chemical identifier for chemical reactions. J Cheminformatics 5(Suppl 1):O16
Google Scholar
Dalby A, Nourse JG, Hounshell WD, Gushurst AKI, Grier DL, Leland BA, Laufer J (1992) Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited. J Chem Inf Comput Sci 32(3):244–255
CAS
Google Scholar
Gobbi A, Lee M-L (2012) Handling of tautomerism and stereochemistry in compound registration. J Chem Inf Model 52(2):285–292
CAS
Google Scholar
Murray-Rust P, Adams S, Downing J, Townsend J, Zhang Y (2011) The semantic architecture of the World-Wide Molecular Matrix (WWMM). J Cheminformatics 3(1):42
CAS
Google Scholar
Tallapragada K, Chewning J, Kombo D, Ludwick B (2012) Making SharePoint chemically aware. J Cheminformatics 4(1):1
CAS
Google Scholar
Townsend J, Murray-Rust P (2011) CMLLite: a design philosophy for CML. J Cheminformatics 3(1):39
CAS
Google Scholar
Cannon EO (2012) New benchmark for chemical nomenclature software. J Chem Inf Model 52(5):1124–1131
CAS
Google Scholar
Drefahl A (2011) CurlySMILES: a chemical language to customize and annotate encodings of molecular and nanodevice structures. J Cheminformatics 3(1):1
CAS
Google Scholar
Gilson MK, Georg G, Wang S (2014) Digital chemistry in the journal of medicinal chemistry. J Med Chem 57(4):1137
CAS
Google Scholar
Weininger D (1988) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 28(1):31–36
CAS
Google Scholar
Weininger D, Weininger A, Weininger JL (1989) SMILES. 2. Algorithm for generation of unique SMILES notation. J Chem Inf Comput Sci 29(2):97–101
CAS
Google Scholar
Ash S, Cline MA, Homer RW, Hurst T, Smith GB (1997) SYBYL Line Notation (SLN): a versatile language for chemical structure representation. J Chem Inf Comput Sci 37(1):71–79
CAS
Google Scholar
Homer RW, Swanson J, Jilek RJ, Hurst T, Clark RD (2008) SYBYL line notation (SLN): a single notation to represent chemical structures, queries, reactions, and virtual libraries. J Chem Inf Model 48(12):2294–2307
CAS
Google Scholar
Warr WA (2010) Tautomerism in chemical information management systems. J Comput Aided Mol Des 24(6–7):497–520
CAS
Google Scholar
Downing J, Murray-Rust P, Tonge AP, Morgan P, Rzepa HS, Cotterill F, Day N, Harvey MJ (2008) SPECTRa: the deposition and validation of primary chemistry research data in digital repositories. J Chem Inf Model 48(8):1571–1581
CAS
Google Scholar
Murray-Rust P, Rzepa H (2011) CML: evolution and design. J Cheminformatics 3(1):44
Google Scholar
Fanton M, Floris M, Cristiani A, Olla S, Medda R, Sabbadin D, Bulfone A, Moro S (2013) MMsDusty: an alternative InChI-based tool to minimize chemical redundancy. Mol Inf 32(8):681–684
CAS
Google Scholar
Gregori-Puigjané E, Garriga-Sust R, Mestres J (2011) Indexing molecules with chemical graph identifiers. J Comput Chem 32(12):2638–2646
Google Scholar
Ihlenfeldt W-D (2012) Comment on “Indexing molecules with chemical graph Identifiers”. J Comput Chem 33(2):237
CAS
Google Scholar
Carbonell P, Carlsson L, Faulon J-L (2013) Stereo signature molecular descriptor. J Chem Inf Model 53(4):887–897
CAS
Google Scholar
Cho YS, No KT, Cho KH (2012) yaInChI: modified InChI string scheme for line notation of chemical structures. SAR QSAR Environ Res 23(3–4):237–255
CAS
Google Scholar
Brown ID, Abrahams SC, Berndt M, Faber J, Karen VL, Motherwell WDS, Villars P, Westbrook JD, McMahon B (2005) Report of the working group on crystal phase identifiers. Acta Crystallogr Sect A: Found Crystallogr A61(6):575–580
CAS
Google Scholar
Coles SJ, Frey JG, Hursthouse MB, Light ME, Milsted AJ, Carr LA, DeRoure D, Gutteridge CJ, Mills HR, Meacham KE, Surridge M, Lyon E, Heery R, Duke M, Day M (2006) An e-science environment for service crystallography from submission to dissemination. J Chem Inf Model 46(3):1006–1016
CAS
Google Scholar
Burgess DR, Manion JA, Hayes CJ (2014) Data formats for elementary gas phase kinetics, Part 1: unique representations of species at the molecular level. Int J Chem Kinet 46(10):640–650
CAS
Google Scholar
Burgess DR, Manion JA, Hayes CJ (2015) Data formats for elementary gas-phase kinetics: Part 2. unique representations of reactions. Int J Chem Kinet 47(5):334–350
CAS
Google Scholar
Chambers J, Davies M, Gaulton A, Papadatos G, Hersey A, Overington J (2014) UniChem: extension of InChI-based compound mapping to salt, connectivity and stereochemistry layers. J Cheminformatics 6(1):43
Google Scholar
Tropsha A, Williams A (2012) How many miles have we gone, InChI by InChI? Chem Int 34(5):33
Google Scholar
Ihlenfeldt W, Bolton E, Bryant S (2009) The PubChem chemical structure sketcher. J Cheminformatics 1(1):20
Google Scholar
Trepalin SV, Yarkov AV, Pletnev IV, Gakh AA (2006) A Java chemical structure editor supporting the modular chemical descriptor language (MCDL). Molecules 11(4):129–141
CAS
Google Scholar
Gakh A, Burnett M, Trepalin S, Yarkov A (2011) Modular chemical descriptor language (MCDL): stereochemical modules. J Cheminformatics 3(1):5
CAS
Google Scholar
BKChem. http://bkchem.zirael.org/index.html. Accessed 17 Apr 2015
Kochev NT, Paskaleva VH, Jeliazkova N (2013) Ambit-Tautomer: an open source tool for tautomer generation. Mol Inf 32(5–6):481–504
CAS
Google Scholar
Sitzmann M, Filippov IV, Nicklaus MC (2008) Internet resources integrating many small-molecules databases. SAR QSAR Environ Res 19(1–2):1–9
CAS
Google Scholar
Kos A, Himmler H-J (2010) CWM global search—the internet search engine for chemists and biologists. Future Internet 2(4):635–644
Google Scholar
Monge A, Arrault A, Marot C, Morin-Allory L (2006) Managing, profiling and analyzing a library of 2.6 million compounds gathered from 32 chemical providers. Mol Divers 10(3):389–403
CAS
Google Scholar
Chepelev L, Dumontier M (2011) Semantic Web integration of cheminformatics resources with the SADI framework. J Cheminformatics 3(1):16
CAS
Google Scholar
Spanton SG, Whittern D (2009) The development of an NMR chemical shift prediction application with the accuracy necessary to grade proton NMR spectra for identity. Magn Reson Chem 47(12):1055–1061
CAS
Google Scholar
Spjuth O, Berg A, Adams S, Willighagen EL (2013) Applications of the InChI in cheminformatics with the CDK and bioclipse. J Cheminformatics 5:14
CAS
Google Scholar
Spjuth O, Eklund M, Ahlberg Helgee E, Boyer S, Carlsson L (2011) Integrated decision support for assessing chemical liabilities. J Chem Inf Model 51(8):1840–1847
CAS
Google Scholar
Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B, Overington JP (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 40(D1):D1100–D1107
CAS
Google Scholar
Hersey A, Chambers J, Bellis L, Patrícia Bento A, Gaulton A, Overington JP (2015) Chemical databases: curation or integration by user-defined equivalence? Drug Discov Today Technol. Online 11 March 2015
Muresan S, Petrov P, Southan C, Kjellberg MJ, Kogej T, Tyrchan C, Varkonyi P, Xie PH (2011) Making every SAR point count: the development of chemistry connect for the large-scale integration of structure and bioactivity data. Drug Discov Today 16(23–24):1019–1030
CAS
Google Scholar
Muresan S, Sitzmann M, Southan C (2012) Mapping between databases of compounds and protein targets. In: Larson RS (ed) Bioinformatics and drug discovery, vol 910. Humana Press, New York, pp 145–164
Google Scholar
Pawson AJ, Sharman JL, Benson HE, Faccenda E, Alexander SPH, Buneman PO, Davenport AP, McGrath JC, Peters JA, Southan C, Spedding M, Yu W, Harmar AJ, NC-IUPHAR (2014) The IUPHAR/BPS guide to pharmacology: an expert-driven knowledgebase of drug targets and their ligands. Nucleic Acids Res 42(D1):D1098–D1106
CAS
Google Scholar
Southan C, Sitzmann M, Muresan S (2013) Comparing the chemical structure and protein content of ChEMBL, DrugBank, human metabolome database and the therapeutic target database. Mol Inf 32(11–12):881–897
CAS
Google Scholar
Wassermann AM, Bajorath J (2011) BindingDB and ChEMBL: online compound databases for drug discovery. Expert Opin Drug Discov 6(7):683–687
CAS
Google Scholar
Willighagen E, Waagmeester A, Spjuth O, Ansell P, Williams A, Tkachenko V, Hastings J, Chen B, Wild D (2013) The ChEMBL database as linked open data. J Cheminformatics 5(1):23
CAS
Google Scholar
Nowotka M, Davies M, Papadatos G, Overington JP (2014) ChEMBL Beaker: a lightweight web framework providing robust and extensible cheminformatics services. Challenges 5(2):444–449
Google Scholar
Rose PW, Beran B, Bi C, Bluhm WF, Dimitropoulos D, Goodsell DS, Prlić A, Quesada M, Quinn GB, Westbrook JD, Young J, Yukich B, Zardecki C, Berman HM, Bourne PE (2011) The RCSB Protein Data Bank: redesigned web site and web services. Nucleic Acids Res 39(Suppl 1):D392–D401
CAS
Google Scholar
Java Native Interface InChI Wrapper http://sourceforge.net/projects/jni-inchi. Accessed 17 Apr 2015
Ninja, an InChI toolkit for Java. http://sourceforge.net/projects/ninja. Accessed 17 Apr 2015
O’Boyle N, Banck M, James C, Morley C, Vandermeersch T, Hutchison G (2011) Open Babel: an open chemical toolbox. J Cheminformatics 3(1):33
Google Scholar
O’Boyle NM, Morley C, Hutchison GR (2008) Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit. Chem Cent J 2:5
Google Scholar
Smith R, Williamson R, Ventura D, Prince J (2013) Rubabel: wrapping open Babel with Ruby. J Cheminformatics 5(1):35
CAS
Google Scholar
Will T, Hutter MC, Jauch J, Helms V (2013) Batch tautomer generation with MolTPC. J Comput Chem 34(28):2485–2492
CAS
Google Scholar
Day AE, Coles SJ, Bird CL, Frey JG, Whitby RJ, Tkachenko VE, Williams AJ (2015) ChemTrove: enabling a generic ELN to support chemistry through the use of transferable plug-ins and online data sources. J Chem Inf Model 55(3):501–509
CAS
Google Scholar
Hettne K, Williams A, van Mulligen E, Kleinjans J, Tkachenko V, Kors J (2010) Automatic versus manual curation of a multi-source chemical dictionary: the impact on text mining. J Cheminformatics 2(1):3
Google Scholar
Williams A, Tkachenko V (2014) The Royal Society of Chemistry and the delivery of chemistry data repositories for the community. J Comput-Aided Mol Des 28(10):1023–1030
CAS
Google Scholar
Haraldsdottir H, Thiele I, Fleming R (2014) Comparative evaluation of open source software for mapping between metabolite identifiers in metabolic network reconstructions: application to Recon 2. J Cheminformatics 6(1):2
Google Scholar
Wohlgemuth G, Haldiya PK, Willighagen E, Kind T, Fiehn O (2010) The Chemical Translation Service-a web-based tool to improve standardization of metabolomic reports. Bioinformatics 26(20):2647–2648
CAS
Google Scholar
O’Boyle NM (2012) Towards a universal SMILES representation—a standard method to generate canonical SMILES based on the InChI. J Cheminformatics 4:22
Google Scholar
Banville DL (ed) (2008) Chemical information mining: facilitating literature-based discovery. CRC Press, Boca Raton
Google Scholar
Jessop D, Adams S, Murray-Rust P (2011) Mining chemical information from open patents. J Cheminformatics 3(1):40
CAS
Google Scholar
Jessop D, Adams S, Willighagen E, Hawizy L, Murray-Rust P (2011) OSCAR4: a flexible architecture for chemical text-mining. J Cheminformatics 3(1):41
CAS
Google Scholar
Klinger R, Kolarik C, Fluck J, Hofmann-Apitius M, Friedrich CM (2008) Detection of IUPAC and IUPAC-like chemical names. Bioinformatics 24(13):i268–i276
CAS
Google Scholar
Kuhn M, Szklarczyk D, Pletscher-Frankild S, Blicher TH, von Mering C, Jensen LJ, Bork P (2014) STITCH 4: integration of protein–chemical interactions with user data. Nucleic Acids Res 42(Database issue):D401–D407
CAS
Google Scholar
Rhodes J, Boyer S, Kreulen J, Chen Y, Ordonez P (2007) Mining patents using molecular similarity search. In: Altman R, Murray T, Klein T, Dunker A, Hunter L (eds) Pacific symposium on biocomputing 2007, Maui, HI, United States, Jan 3–7, 2007. World Scientific Publishing Company, Singapore, pp 304–315
Google Scholar
Southan C, Stracz A (2013) Extracting and connecting chemical structures from text sources using chemicalize.org. J Cheminformatics 5:20
CAS
Google Scholar
Williams AJ, Yerin A (2008) Automated identification and conversion of chemical names to structure-searchable information. In: Banville DL (ed) Chemical information mining. CRC Press, Boca Raton, pp 21–44
Google Scholar
Zimmermann M, Fluck J, Thi LT, Kolarik C, Kumpf K, Hofmann M (2005) Information extraction in the life sciences: perspective for medicinal chemistry, pharmacology and toxicology. Curr Top Med Chem 5(8):785–796
CAS
Google Scholar
Hettne KM, Stierum RH, Schuemie MJ, Hendriksen PJM, Schijvenaars BJA, Mulligen EMv, Kleinjans J, Kors JA (2009) A dictionary to identify small molecules and drugs in free text. Bioinformatics 25(22):2983–2991
CAS
Google Scholar
McDaniel JR, Balmuth JR (1992) Kekule: OCR-optical chemical (structure) recognition. J Chem Inf Comput Sci 32(4):373–378
CAS
Google Scholar
Park J, Rosania G, Shedden K, Nguyen M, Lyu N, Saitou K (2009) Automated extraction of chemical structure information from digital raster images. Chem Cent J 3(1):1–16
CAS
Google Scholar
Simon A, Johnson AP (1997) Recent advances in the CLiDE project: logical layout analysis of chemical documents. J Chem Inf Comput Sci 37(1):109–116
CAS
Google Scholar
Valko AT, Johnson AP (2009) CLiDE Pro: the latest generation of CLiDE, a tool for optical chemical structure recognition. J Chem Inf Model 49(4):780–787
CAS
Google Scholar
Zimmermann M (2007) Über die Kunst, dem Rechner das Lesen beizubringen. (The art of teaching the computer to read). Nachr Chem 55(10):997–999
CAS
Google Scholar
Filippov IV, Nicklaus MC (2009) Optical structure recognition software to recover chemical information: OSRA, an open source solution. J Chem Inf Model 49(3):740–743
CAS
Google Scholar
Williams AJ, Yerin A (2013) Automated systematic nomenclature generation for organic compounds. Wiley Interdiscip Rev Comput Mol Sci 3(2):150–160
CAS
Google Scholar
Bachrach S (2009) Chemistry publication—making the revolution. J Cheminformatics 1(1):2
Google Scholar
Borkum M, Frey J (2014) Usage and applications of Semantic Web techniques and technologies to support chemistry research. J Cheminformatics 6(1):18
Google Scholar
Casher O, Rzepa HS (2006) Semanticeye: a Semantic Web application to rationalize and enhance chemical electronic publishing. J Chem Inf Model 46(6):2396–2411
CAS
Google Scholar
Casher O, Rzepa HS (2010) Using semantically-enabled components for social web-based scientific collaborations. In: Belford RE, Moore JW, Pence HE (eds) Enhancing learning with online resources, social networking, and digital libraries, ACS symposium series, vol 1060. American Chemical Society, Washington, pp 41–63
Google Scholar
Chen B, Ding Y, Wild D (2012) Improving integrative searching of systems chemical biology data using semantic annotation. J Cheminformatics 4(1):6
CAS
Google Scholar
Chepelev L, Dumontier M (2011) Chemical Entity Semantic Specification: knowledge representation for efficient semantic cheminformatics and facile data integration. J Cheminformatics 3(1):20
CAS
Google Scholar
Choi J, Davis MJ, Newman AF, Ragan MA (2010) A Semantic Web ontology for small molecules and their biological targets. J Chem Inf Model 50(5):732–741
CAS
Google Scholar
Coles SJ, Day NE, Murray-Rust P, Rzepa HS, Zhang Y (2005) Enhancement of the chemical semantic web through the use of InChI identifiers. Org Biomol Chem 3(10):1832–1834
CAS
Google Scholar
Frey J, De Roure D, Taylor K, Essex J, Mills H, Zaluska E (2006) CombeChem: a case study in provenance and annotation using the Semantic Web. In: Moreau L, Foster I (eds) Provenance and annotation of data, vol 4145. Springer, Berlin, pp 270–277
Google Scholar
Frey JG (2009) The value of the Semantic Web in the laboratory. Drug Discov Today 14(11–12):552–561
Google Scholar
Frey JG, Bird CL (2013) Cheminformatics and the Semantic Web: adding value with linked data and enhanced provenance. Wiley Interdiscip Rev Comput Mol Sci 3(5):465–481
CAS
Google Scholar
Murray-Rust P, Mitchell JBO, Rzepa HS (2005) Communication and re-use of chemical information in bioscience. BMC Bioinf 6:180
Google Scholar
Murray-Rust P, Rzepa HS, Tyrrell SM, Zhang Y (2004) Representation and use of chemistry in the global electronic age. Org Biomol Chem 2(22):3192–3203
CAS
Google Scholar
O’Boyle N, Guha R, Willighagen E, Adams S, Alvarsson J, Bradley J-C, Filippov I, Hanson R, Hanwell M, Hutchison G, James C, Jeliazkova N, Lang A, Langner K, Lonie D, Lowe D, Pansanel J, Pavlov D, Spjuth O, Steinbeck C, Tenderholt A, Theisen K, Murray-Rust P (2011) Open data, open source and open standards in chemistry: the Blue Obelisk 5 years on. J Cheminformatics 3(1):37
Google Scholar
Prasanna MD, Vondrasek J, Wlodawer A, Rodriguez H, Bhat TN (2006) Chemical compound navigator: a web-based chem-BLAST, chemical taxonomy-based search engine for browsing compounds. Proteins Struct Funct Bioinf 63(4):907–917
CAS
Google Scholar
Samwald M, Jentzsch A, Bouton C, Kallesoe C, Willighagen E, Hajagos J, Marshall M, Prud’hommeaux E, Hassanzadeh O, Pichler E, Stephens S (2011) Linked open drug data for pharmaceutical research and development. J Cheminformatics 3(1):19
Google Scholar
Tanaka K, Aoki-Kinoshita KF, Kotera M, Sawaki H, Tsuchiya S, Fujita N, Shikanai T, Kato M, Kawano S, Yamada I, Narimatsu H (2014) WURCS: the Web3 unique representation of carbohydrate structures. J Chem Inf Model 54(6):1558–1566
CAS
Google Scholar
Taylor KR, Gledhill RJ, Essex JW, Frey JG, Harris SW, De Roure DC (2006) Bringing chemical data onto the Semantic Web. J Chem Inf Model 46(3):939–952
CAS
Google Scholar
Teixeira AL, Falcao AO (2013) Noncontiguous atom matching structural similarity function. J Chem Inf Model 53(10):2511–2524
CAS
Google Scholar
Velden T, Lagoze C (2009) Communicating chemistry. Nat Chem 1(9):673–678
CAS
Google Scholar
Williams AJ (2008) Internet-based tools for communication and collaboration in chemistry. Drug Discov Today 13(11–12):502–506
CAS
Google Scholar
Williams AJ (2008) Public chemical compound databases. Curr Opin Drug Discov Dev 11(3):393–404
CAS
Google Scholar
Willighagen EL, Alvarsson J, Andersson A, Eklund M, Lampa S, Lapins M, Spjuth O, Wikberg JES (2011) Linking the resource description framework to cheminformatics and proteochemometrics. J Biomed Semant 2(Suppl 1):S6
Google Scholar
Goldmann D, Montanari F, Richter L, Zdrazil B, Ecker GF (2014) Exploiting open data: a new era in pharmacoinformatics. Future Med Chem 6(5):503–514
CAS
Google Scholar
Williams AJ, Harland L, Groth P, Pettifer S, Chichester C, Willighagen EL, Evelo CT, Blomberg N, Ecker G, Goble C, Mons B (2012) Open PHACTS: semantic interoperability for drug discovery. Drug Discov Today 17(21–22):1188–1198
Google Scholar
Sharman JL, Mpamhanga CP, Spedding M, Germain P, Staels B, Dacquet C, Laudet V, Harmar AJ (2011) IUPHAR-DB: new receptors and tools for easy searching and visualization of pharmacological data. Nucleic Acids Res 39(Suppl 1):D534–D538
CAS
Google Scholar
Southan C, Boppana K, Jagarlapudi S, Muresan S (2011) Analysis of in vitro bioactivity data extracted from drug discovery literature and patents: ranking 1654 human protein targets by assayed compounds and molecular scaffolds. J Cheminformatics 3(1):14
Google Scholar
Tiikkainen P, Franke L (2012) Analysis of commercial and public bioactivity databases. J Chem Inf Model 52(2):319–326
CAS
Google Scholar
Southan C (2015) Expanding opportunities for mining bioactive chemistry from patents. Drug Discov Today Technol (in press)
Bobach C, Bohme T, Laube U, Puschel A, Weber L (2012) Automated compound classification using a chemical ontology. J Cheminformatics 4(1):40
CAS
Google Scholar
de Matos P, Alcántara R, Dekker A, Ennis M, Hastings J, Haug K, Spiteri I, Turner S, Steinbeck C (2010) Chemical entities of biological interest: an update. Nucleic Acids Res 38(Suppl 1):D249–D254
Google Scholar
Degtyarenko K, de Matos P, Ennis M, Hastings J, Zbinden M, McNaught A, Alcántara R, Darsow M, Guedj M, Ashburner M (2008) ChEBI: a database and ontology for chemical entities of biological interest. Nucleic Acids Res 36(Suppl 1):D344–D350
CAS
Google Scholar
Degtyarenko K, Ennis M, Garavelli JS (2007) “Good annotation practice” for chemical data in biology. Silico Biol 7(Suppl 2):45–56
Google Scholar
Degtyarenko K, Hastings J, de Matos P, Ennis M (2009) ChEBI: an open bioinformatics and cheminformatics resource. In: Bateman A, Draghici S, Pearson WR, Stein LD, Yates JR (eds) Current protocols in bioinformatics, vol 26. Wiley, Oxford, pp 14.19.11–14.19.20
Hardy B, Douglas N, Helma C, Rautenberg M, Jeliazkova N, Jeliazkov V, Nikolova I, Benigni R, Tcheremenskaia O, Kramer S, Girschick T, Buchwald F, Wicker J, Karwath A, Gutlein M, Maunz A, Sarimveis H, Melagraki G, Afantitis A, Sopasakis P, Gallagher D, Poroikov V, Filimonov D, Zakharov A, Lagunin A, Gloriozova T, Novikov S, Skvortsova N, Druzhilovsky D, Chawla S, Ghosh I, Ray S, Patel H, Escher S (2010) Collaborative development of predictive toxicology applications. J Cheminformatics 2(1):7
Google Scholar
Hastings J, Josephs Z, Steinbeck C (2012) Accessing and using chemical property databases. In: Reisfeld B, Mayeno AN (eds) Computational toxicology, vol 929. Humana Press, New York, pp 193–219
Google Scholar
Hastings J, Magka D, Batchelor C, Duan L, Stevens R, Ennis M, Steinbeck C (2012) Structure-based classification and ontology in chemistry. J Cheminformatics 4(1):8
CAS
Google Scholar
Haug K, Salek RM, Conesa P, Hastings J, de Matos P, Rijnbeek M, Mahendraker T, Williams M, Neumann S, Rocca-Serra P, Maguire E, González-Beltrán A, Sansone S-A, Griffin JL, Steinbeck C (2013) MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res 41(D1):D781–D786
CAS
Google Scholar
Brown M, Dunn WB, Dobson P, Patel Y, Winder CL, Francis-McIntyre S, Begley P, Carroll K, Broadhurst D, Tseng A, Swainston N, Spasic I, Goodacre R, Kell DB (2009) Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. Analyst 134(7):1322–1332
CAS
Google Scholar
Carroll AJ (2012) Online metabolomics databases and pipelines. In: Roessner U (ed) metabolomics. InTech, Rijeka, pp 47–72
Google Scholar
Carroll AJ, Badger MR, Millar AH (2010) The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets. BMC Bioinf 11:376
Google Scholar
Fiehn O, Kind T, Barupal DK (2011) Data processing, metabolomic databases and pathway analysis. In: Hall RD (ed) Biology of plant metabolomics annual plant review, vol 43. Wiley, Oxford, pp 367–406
Google Scholar
Hummel J, Selbig J, Walther D, Kopka J (2007) The Golm metabolome database: a database for GC–MS based metabolite profiling. In: Nielsen J, Jewett M (eds) Metabolomics, vol 18. Springer, Berlin, pp 75–95
Google Scholar
Jenkins H, Hardy N, Beckmann M, Draper J, Smith AR, Taylor J, Fiehn O, Goodacre R, Bino RJ, Hall R, Kopka J, Lane GA, Lange BM, Liu JR, Mendes P, Nikolau BJ, Oliver SG, Paton NW, Rhee S, Roessner-Tunali U, Saito K, Smedsgaard J, Sumner LW, Wang T, Walsh S, Wurtele ES, Kell DB (2004) A proposed framework for the description of plant metabolomics experiments and their results. Nat Biotech 22(12):1601–1606
CAS
Google Scholar
Johnson SR, Lange BM (2015) Open-access metabolomics databases for natural product research: present capabilities and future potential. Front Bioeng Biotechnol 3:22
Google Scholar
Kind T, Scholz M, Fiehn O (2009) How large is the metabolome? A critical analysis of data exchange practices in chemistry. PLoS One 4(5):e5440
Google Scholar
Ludwig C, Easton J, Lodi A, Tiziani S, Manzoor S, Southam A, Byrne J, Bishop L, He S, Arvanitis T, Günther U, Viant M (2012) Birmingham Metabolite Library: a publicly accessible database of 1-D 1H and 2-D 1H J-resolved NMR spectra of authentic metabolite standards (BML-NMR). Metabolomics 8(1):8–18
CAS
Google Scholar
May JW, James AG, Steinbeck C (2013) Metingear: a development environment for annotating genome-scale metabolic models. Bioinformatics 29(17):2213–2215
CAS
Google Scholar
Moco S, Vervoort J, Moco S, Bino RJ, De Vos RCH, Bino R (2007) Metabolomics technologies and metabolite identification. TrAC Trends Anal Chem 26(9):855–866
CAS
Google Scholar
Peironcely J, Rojas-Cherto M, Fichera D, Reijmers T, Coulier L, Faulon J-L, Hankemeier T (2012) OMG: open molecule generator. J Cheminformatics 4(1):21
CAS
Google Scholar
Redestig H, Kusano M, Fukushima A, Matsuda F, Saito K, Arita M (2010) Consolidating metabolite identifiers to enable contextual and multi-platform metabolomics data analysis. BMC Bioinf 11:214
Google Scholar
Rojas-Chertó M, van Vliet M, Peironcely JE, van Doorn R, Kooyman M, te Beek T, van Driel MA, Hankemeier T, Reijmers T (2012) MetiTree: a web application to organize and process high-resolution multi-stage mass spectrometry metabolomics data. Bioinformatics 28(20):2707–2709
Google Scholar
Schymanski EL, Neumann S (2013) CASMI: and the winner is. Metabolites 3(2):412–439
CAS
Google Scholar
Steinbeck C, Conesa P, Haug K, Mahendraker T, Williams M, Maguire E, Rocca-Serra P, Sansone S-A, Salek R, Griffin J (2012) MetaboLights: towards a new COSMOS of metabolomics data management. Metabolomics 8(5):757–760
CAS
Google Scholar
Sumner L, Amberg A, Barrett D, Beale M, Beger R, Daykin C, Fan TM, Fiehn O, Goodacre R, Griffin J, Hankemeier T, Hardy N, Harnly J, Higashi R, Kopka J, Lane A, Lindon J, Marriott P, Nicholls A, Reily M, Thaden J, Viant M (2007) Proposed minimum reporting standards for chemical analysis. Metabolomics 3(3):211–221
CAS
Google Scholar
Wishart DS (2009) Computational strategies for metabolite identification in metabolomics. Bioanalysis 1(9):1579–1596
CAS
Google Scholar
Wishart DS (2011) Advances in metabolite identification. Bioanalysis 3(15):1769–1782
CAS
Google Scholar
Mu F, Williams RF, Unkefer CJ, Unkefer PJ, Faeder JR, Hlavacek WS (2007) Carbon-fate maps for metabolic reactions. Bioinformatics 23(23):3193–3199
CAS
Google Scholar
Zhou B, Wang J, Ressom HW (2012) MetaboSearch: tool for mass-based metabolite identification using multiple databases. PLoS One 7(6):e40096
CAS
Google Scholar
Zhou B, Xiao JF, Ressom HW (2013) Prioritization of putative metabolite identifications in LC-MS/MS experiments using a computational pipeline. Proteomics 13(2):248–260
CAS
Google Scholar
Nöh K, Droste P, Wiechert W (2015) visual workflows for 13C-metabolic flux analysis. Bioinformatics 31(3):346–354
Google Scholar
Steinbeck C, Krause S, Kuhn S (2003) NMRShiftDB—constructing a free chemical information system with open-source components. J Chem Inf Comput Sci 43(6):1733–1739
CAS
Google Scholar
The CSEARCH NMRpredict server. http://nmrpredict.orc.univie.ac.at/. Accessed 19 Apr 2015
Kalchhauser H, Robien W (1985) CSEARCH: a computer program for identification of organic compounds and fully automated assignment of carbon-13 nuclear magnetic resonance spectra. J Chem Inf Comput Sci 25(2):103–108
CAS
Google Scholar
Kuhn S, Schlörer Nils E (2012) Strukturaufklärung mit NMR in der Synthesechemie. Nachr Chem 60(11):1106–1107
CAS
Google Scholar
Plainchont B, de Emerenciano Paulo V, Nuzillard J-M (2013) Recent advances in the structure elucidation of small organic molecules by the LSD software. Magn Reson Chem 51(8):447–453
CAS
Google Scholar
Steinbeck C, Kuhn S (2004) NMRShiftDB – compound identification and structure elucidation support through a free community-built web database. Phytochemistry 65(19):2711–2717
CAS
Google Scholar
Ahmed L, Rasulev B, Turabekova M, Leszczynska D, Leszczynski J (2013) Receptor- and ligand-based study of fullerene analogues: comprehensive computational approach including quantum-chemical, QSAR and molecular docking simulations. Org Biomol Chem 11(35):5798–5808
CAS
Google Scholar
Benz RD (2007) Toxicological and clinical computational analysis and the US FDA/CDER. Expert Opin Drug Metab Toxicol 3(1):109–124
CAS
Google Scholar
Bertinetto C, Duce C, Micheli A, Solaro R, Starita A, Tine MR (2007) Prediction of the glass transition temperature of (meth)acrylic polymers containing phenyl groups by recursive neural network. Polymer 48(24):7121–7129
CAS
Google Scholar
Bertinetto C, Duce C, Micheli A, Solaro R, Starita A, Tiné MR (2009) Evaluation of hierarchical structured representations for QSPR studies of small molecules and polymers by recursive neural networks. J Mol Graph Model 27(7):797–802
CAS
Google Scholar
Chavan S, Nicholls IA, Karlsson BCG, Rosengren AM, Ballabio D, Consonni V, Todeschini R (2014) Towards global QSAR model building for acute toxicity: munro database case study. Int J Mol Sci 15(10):18162–18174
CAS
Google Scholar
Richard AM (2006) Future of toxicology—predictive toxicology: an expanded view of “chemical toxicity”. Chem Res Toxicol 19(10):1257–1262
CAS
Google Scholar
Richard AM, Gold LS, Nicklaus MC (2006) Chemical structure indexing of toxicity data on the Internet: moving toward a flat world. Curr Opin Drug Discov Dev 9(3):314–325
CAS
Google Scholar
Ruusmann V, Sild S, Maran U (2014) QSAR DataBank—an approach for the digital organization and archiving of QSAR model information. J Cheminformatics 6(1):25
Google Scholar
Spjuth O, Willighagen E, Guha R, Eklund M, Wikberg J (2010) Towards interoperable and reproducible QSAR analyses: exchange of datasets. J Cheminformatics 2(1):5
Google Scholar
Sushko Y, Novotarskyi S, Korner R, Vogt J, Abdelaziz A, Tetko I (2014) Prediction-driven matched molecular pairs to interpret QSARs and aid the molecular optimization process. J Cheminformatics 6(1):48
Google Scholar
Toropov A, Toropova A, Benfenati E, Leszczynska D, Leszczynski J (2010) Use of the international chemical identifier for constructing QSPR-model of normal boiling points of acyclic carbonyl substances. J Math Chem 47(1):355–369
CAS
Google Scholar
Toropov AA, Toropova AP, Benfenati E (2009) QSPR modeling of octanol water partition coefficient of platinum complexes by InChI-based optimal descriptors. J Math Chem 46(4):1060–1073
CAS
Google Scholar
Toropov AA, Toropova AP, Benfenati E (2010) QSAR-modeling of toxicity of organometallic compounds by means of the balance of correlations for InChI-based optimal descriptors. Mol Diversity 14(1):183–192
CAS
Google Scholar
Toropov AA, Toropova AP, Benfenati E, Leszczynska D, Leszczynski J (2009) Additive InChI-based optimal descriptors: QSPR modeling of fullerene C60 solubility in organic solvents. J Math Chem 46(4):1232–1251
CAS
Google Scholar
Toropov AA, Toropova AP, Benfenati E, Leszczynska D, Leszczynski J (2010) InChI-based optimal descriptors: QSAR analysis of fullerene[C60]-based HIV-1 PR inhibitors by correlation balance. Eur J Med Chem 45(4):1387–1394
CAS
Google Scholar
Toropova AP, Toropov AA, Benfenati E, Gini G (2011) Simplified molecular input-line entry system and international chemical identifier in the QSAR analysis of styrylquinoline derivatives as HIV-1 integrase inhibitors. Chem Biol Drug Des 77(5):343–360
CAS
Google Scholar
Zakharov AV, Peach ML, Sitzmann M, Nicklaus MC (2014) A new approach to radial basis function approximation and its application to QSAR. J Chem Inf Model 54(3):713–719
CAS
Google Scholar
Langham JJ, Jain AN (2008) Accurate and interpretable computational modeling of chemical mutagenicity. J Chem Inf Model 48(9):1833–1839
CAS
Google Scholar
Arvidson KB (2008) FDA toxicity databases and real-time data entry. Toxicol Appl Pharmacol 233(1):17–19
CAS
Google Scholar
Fostel JM (2008) Towards standards for data exchange and integration and their impact on a public database such as CEBS (chemical effects in biological systems). Toxicol Appl Pharmacol 233(1):54–62
CAS
Google Scholar
Jeliazkova N, Jeliazkov V (2011) AMBIT RESTful web services: an implementation of the OpenTox application programming interface. J Cheminformatics 3(1):18
CAS
Google Scholar
Kinjo AR, Nakamura H (2009) Comprehensive structural classification of ligand-binding motifs in proteins. Structure 17(2):234–246
CAS
Google Scholar
Kiss R, Sándor M, Gere A, Schmidt É, Balogh GT, Kiss B, Molnár L, Lemmen C, Keserű GM (2012) Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. J Chem Inf Model 52(1):233–242
CAS
Google Scholar
Liu Y, Li F, Sun H (2014) Thermal decomposition of FOX-7 studied by ab initio molecular dynamics simulations. Theor Chem Acc 133(10):1–11
Google Scholar
Murray-Rust P, Rzepa HS, Stewart JJP, Zhang Y (2005) A global resource for computational chemistry. J Mol Model 11(6):532–541
CAS
Google Scholar
Nashev LG, Schuster D, Laggner C, Sodha S, Langer T, Wolber G, Odermatt A (2010) The UV-filter benzophenone-1 inhibits 17β-hydroxysteroid dehydrogenase type 3: virtual screening as a strategy to identify potential endocrine disrupting chemicals. Biochem Pharmacol 79(8):1189–1199
CAS
Google Scholar
Phadungsukanan W, Shekar S, Shirley R, Sander M, West RH, Kraft M (2009) First-principles thermochemistry for silicon species in the decomposition of tetraethoxysilane. J Phys Chem A 113(31):9041–9049
CAS
Google Scholar
Qu X, Jain A, Rajput NN, Cheng L, Zhang Y, Ong SP, Brafman M, Maginn E, Curtiss LA, Persson KA (2015) The Electrolyte Genome project: a big data approach in battery materials discovery. Comput Mater Sci 103:56–67
CAS
Google Scholar
Shirley R, Phadungsukanan W, Kraft M, Downing J, Day NE, Murray-Rust P (2010) First-principles thermochemistry for gas phase species in an industrial rutile chlorinator. J Phys Chem A 114(43):11825–11832
CAS
Google Scholar
Totton TS, Shirley R, Kraft M (2011) First-principles thermochemistry for the combustion of in a methane flame. Proc Combust Inst 33(1):493–500
CAS
Google Scholar
Martin E, Monge A, Duret J-A, Gualandi F, Peitsch M, Pospisil P (2012) Building an R&D chemical registration system. J Cheminformatics 4(1):11
CAS
Google Scholar
Cass ME, Rzepa HS, Rzepa DR, Williams CK (2005) The use of the free, open-source program Jmol to generate an interactive web site to teach molecular symmetry. J Chem Educ 82(11):1736
CAS
Google Scholar
Gledhill R, Kent S, Hudson B, Richards WG, Essex JW, Frey JG (2006) A computer-aided drug discovery system for chemistry teaching. J Chem Inf Model 46(3):960–970
CAS
Google Scholar
Kraut H, Eiblmaier J, Grethe G, Loew P, Matuszczyk H, Saller H (2013) Algorithm for reaction classification. J Chem Inf Model 53(11):2884–2895
CAS
Google Scholar
Currano JN (2014) Reaction searching. In: Currano JN, Roth DL (eds) Chemical information for chemists: a primer. The Royal Society of Chemistry, Cambridge, pp 224–254
Google Scholar
Lawson AJ, Swienty-Busch J, Géoui T, Evans D (2014) The making of Reaxys? Towards unobstructed access to relevant chemistry information. In: McEwen LR, Buntrock RE (eds) The future of the history of chemical information, ACS symposium series, vol 1164. American Chemical Society, Washington, pp 127–148
Google Scholar
McEwen LR, Buntrock RE (eds) (2014) The future of the history of chemical information, ACS symposium series, vol 1164. American Chemical Society, Washington
Google Scholar
Bolton EE, Wang Y, Thiessen PA, Bryant SH (2008) PubChem: integrated platform of small molecules and biological activities. In: Ralph AW, David CS (eds) Annual Reports in Computational Chemistry, vol 4. Elsevier, Amsterdam, pp 217–241
Google Scholar
Huang R, Southall N, Wang Y, Yasgar A, Shinn P, Jadhav A, Nguyen D-T, Austin CP (2011) The NCGC Pharmaceutical Collection: a comprehensive resource of clinically approved drugs enabling repurposing and chemical genomics. Sci Transl Med 3(80):80ps16
Google Scholar
Liu T, Lin Y, Wen X, Jorissen RN, Gilson MK (2007) BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities. Nucleic Acids Res 35(Suppl 1):D198–D201
CAS
Google Scholar
Yadav IS, Singh H, Mohd IK, Chaudhury A, Raghava GPS, Agarwal SM (2014) EGFRIndb: epidermal growth factor receptor inhibitor database. Anti-Cancer Agents Med Chem 14(7):928–935
CAS
Google Scholar
Law V, Knox C, Djoumbou Y, Jewison T, Guo AC, Liu Y, Maciejewski A, Arndt D, Wilson M, Neveu V, Tang A, Gabriel G, Ly C, Adamjee S, Dame ZT, Han B, Zhou Y, Wishart DS (2014) DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res 42(D1):D1091–D1097
CAS
Google Scholar
Wishart DS (2010) DrugBank: a general resource for pharmaceutical and pharmacological research. Mol Cell Pharmacol 2(1):25–38
CAS
Google Scholar
Seiler KP, George GA, Happ MP, Bodycombe NE, Carrinski HA, Norton S, Brudz S, Sullivan JP, Muhlich J, Serrano M, Ferraiolo P, Tolliday NJ, Schreiber SL, Clemons PA (2008) ChemBank: a small-molecule screening and cheminformatics resource database. Nucleic Acids Res 36(Suppl 1):D351–D359
CAS
Google Scholar
Zhang C, Tao L, Qin C, Zhang P, Chen S, Zeng X, Xu F, Chen Z, Yang S, Chen Y (2015) CFam: a chemical families database based on iterative selection of functional seeds and seed-directed compound clustering. Nucleic Acids Res 43(D1):D558–D565
Google Scholar
Finn RD, Miller BL, Clements J, Bateman A (2014) iPfam: a database of protein family and domain interactions found in the Protein Data Bank. Nucleic Acids Res 42(D1):D364–D373
CAS
Google Scholar
Henrick K, Feng Z, Bluhm WF, Dimitropoulos D, Doreleijers JF, Dutta S, Flippen-Anderson JL, Ionides J, Kamada C, Krissinel E, Lawson CL, Markley JL, Nakamura H, Newman R, Shimizu Y, Swaminathan J, Velankar S, Ory J, Ulrich EL, Vranken W, Westbrook J, Yamashita R, Yang H, Young J, Yousufuddin M, Berman HM (2008) Remediation of the Protein Data Bank archive. Nucleic Acids Res 36(Suppl 1):D426–D433
CAS
Google Scholar
Ivan G, Szabadka Z, Grolmusz V (2009) On the asymmetry of the residue compositions of the binding sites on protein surfaces. J Bioinf Comput Biol 07(06):931–938
CAS
Google Scholar
Ivan G, Szabadka Z, Grolmusz V (2010) Cysteine and tryptophan anomalies found when scanning all the binding sites in the Protein Data Bank. Int J Bioinf Res Appl 6(6):594–608
CAS
Google Scholar
Iván G, Szabadka Z, Grolmusz V (2007) Being a binding site: characterizing residue composition of binding sites on proteins. Bioinformation 2(5):216–221
Google Scholar
Sen S, Young J, Berrisford JM, Chen M, Conroy MJ, Dutta S, Di Costanzo L, Gao G, Ghosh S, Hudson BP, Igarashi R, Kengaku Y, Liang Y, Peisach E, Persikova I, Mukhopadhyay A, Narayanan BC, Sahni G, Sato J, Sekharan M, Shao C, Tan L, Zhuravleva MA (2014) Small molecule annotation for the Protein Data Bank. Database 2014:bau116
Westbrook JD, Shao C, Feng Z, Zhuravleva M, Valenkar S, Young J (2015) The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the protein Data Bank. Bioinformatics 31:1274–1278
Google Scholar
Ordog R, Szabadka Z, Grolmusz V (2008) Analyzing the simplicial decomposition of spatial protein structures. BMC Bioinf 9(Suppl 1):S11
Google Scholar
Szabadka Z, Grolmusz V (2006) Building a structured PDB: the RS-PDB database. Conf Proc IEEE Eng Med Biol Soc 1:5755–5758
Google Scholar
Szabadka Z, Grolmusz V (2007) High throughput processing of the structural information in the Protein Data Bank. J Mol Graphics Modell 25(6):831–836
CAS
Google Scholar
Prasanna MD, Vondrasek J, Wlodawer A, Bhat TN (2005) Application of InChI to curate, index, and query 3-D structures. Proteins Struct Funct Bioinf 60(1):1–4
CAS
Google Scholar
Barthelmes J, Ebeling C, Chang A, Schomburg I, Schomburg D (2007) BRENDA, AMENDA and FRENDA: the enzyme information system in 2007. Nucleic Acids Res 35(Suppl 1):D511–D514
CAS
Google Scholar
Schomburg I, Chang A, Placzek S, Söhngen C, Rother M, Lang M, Munaretto C, Ulas S, Stelzer M, Grote A, Scheer M, Schomburg D (2013) BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA. Nucleic Acids Res 41(D1):D764–D772
CAS
Google Scholar
Carugo O, Eisenhaber F (eds) (2010) Data mining techniques for the life sciences. Humana Press, New York
Google Scholar
Bernard T, Bridge A, Morgat A, Moretti S, Xenarios I, Pagni M (2014) Reconciliation of metabolites and biochemical reactions for metabolic networks. Briefings Bioinf 15(1):123–135
Google Scholar
Lang M, Stelzer M, Schomburg D (2011) BKM-react, an integrated biochemical reaction database. BMC Biochem 12:42
CAS
Google Scholar
Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, Djoumbou Y, Mandal R, Aziat F, Dong E, Bouatra S, Sinelnikov I, Arndt D, Xia J, Liu P, Yallou F, Bjorndahl T, Perez-Pineiro R, Eisner R, Allen F, Neveu V, Greiner R, Scalbert A (2013) HMDB 3.0—the human metabolome database in 2013. Nucleic Acids Res 41(D1):D801–D807
CAS
Google Scholar
Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, Hau DD, Psychogios N, Dong E, Bouatra S, Mandal R, Sinelnikov I, Xia J, Jia L, Cruz JA, Lim E, Sobsey CA, Shrivastava S, Huang P, Liu P, Fang L, Peng J, Fradette R, Cheng D, Tzur D, Clements M, Lewis A, De Souza A, Zuniga A, Dawe M, Xiong Y, Clive D, Greiner R, Nazyrova A, Shaykhutdinov R, Li L, Vogel HJ, Forsythe I (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37(Suppl 1):D603–D610
CAS
Google Scholar
Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, Fung C, Nikolai L, Lewis M, Coutouly M-A, Forsythe I, Tang P, Shrivastava S, Jeroncic K, Stothard P, Amegbey G, Block D, Hau DD, Wagner J, Miniaci J, Clements M, Gebremedhin M, Guo N, Zhang Y, Duggan GE, MacInnis GD, Weljie AM, Dowlatabadi R, Bamforth F, Clive D, Greiner R, Li L, Marrie T, Sykes BD, Vogel HJ, Querengesser L (2007) HMDB: the Human Metabolome Database. Nucleic Acids Res 35(Suppl 1):D521–D526
CAS
Google Scholar
Maeda MH, Kondo K (2013) Three-dimensional structure database of natural metabolites (3DMET): a novel database of curated 3D structures. J Chem Inf Model 53(3):527–533
CAS
Google Scholar
Altman T, Travers M, Kothari A, Caspi R, Karp PD (2013) A systematic comparison of the MetaCyc and KEGG pathway databases. BMC Bioinf 14:112
Google Scholar
Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2011) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40(D1):D109–D114
Fahy E, Cotter D, Sud M (1811) Subramaniam S (2011) Lipid classification, structures and tools. Biochim Biophys Acta Mol Cell Biol Lipids 11:637–647
Google Scholar
Murphy RC, Fahy E (2010) Isoprostane nomenclature: more suggestions. Prostaglandins Leukot Essent Fatty Acids 82(2):69–70
CAS
Google Scholar
Nielsen J (2009) Systems biology of lipid metabolism: from yeast to human. FEBS Lett 583(24):3905–3913
CAS
Google Scholar
Davis GDJ, Vasanthi AHR (2011) Seaweed metabolite database (SWMD): a database of natural compounds from marine algae. Bioinformation 5(8):361–364
Google Scholar
Herrgard MJ, Swainston N, Dobson P, Dunn WB, Arga KY, Arvas M, Buethgen N, Borger S, Costenoble R, Heinemann M, Hucka M, Le Novere N, Li P, Liebermeister W, Mo ML, Oliveira AP, Petranovic D, Pettifer S, Simeonidis E, Smallbone K, Spasie I, Weichart D, Brent R, Broomhead DS, Westerhoff HV, Kuerdar B, Penttilae M, Klipp E, Palsson BO, Sauer U, Oliver SG, Mendes P, Nielsen J, Kell DB (2008) A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol 26(10):1155–1160
CAS
Google Scholar
Stobbe MD, Houten SM, Jansen GA, van Kampen AHC, Moerland PD (2011) Critical assessment of human metabolic pathway databases: a stepping stone for future integration. BMC Syst Biol 5:165
Google Scholar
Stobbe MD, Swertz MA, Thiele I, Rengaw T, van Kampen AHC, Moerland PD (2013) Consensus and conflict cards for metabolic pathway databases. BMC Syst Biol 7:50
Google Scholar
Barth A (1993) SpecInfo: an integrated spectroscopic information system. J Chem Inf Comput Sci 33(1):52–58
CAS
Google Scholar
Bremser W, Grzonka M (1991) SpecInfo—a multidimensional spectroscopic interpretation system. Microchim Acta 104(1–6):483–491
Google Scholar
Ba YA, Wenger C, Surleau R, Boudon V, Rotger M, Daumont L, Bonhommeau DA, Tyuterev VG, Dubernet M-L (2013) MeCaSDa and ECaSDa: methane and ethene calculated spectroscopic databases for the virtual atomic and molecular data centre. J Quant Spectrosc Radiat Transf 130:62–68
CAS
Google Scholar
Dunkel R, Wu X (2007) Identification of organic molecules from a structure database using proton and carbon NMR analysis results. J Magn Reson 188(1):97–110
CAS
Google Scholar
Hill C, Gordon IE, Rothman LS, Tennyson J (2013) A new relational database structure and online interface for the HITRAN database. J Quant Spectrosc Radiat Transf 130:51–61
CAS
Google Scholar
Wiley’s Compound Search. http://www.compoundsearch.com/. Accessed 21 Apr 2015
Linstrom PJ, Mallard WG (eds) In: NIST chemistry webbook, NIST standard reference database number 69. National Institute of Standards and Technology, Gaithersburg. http://webbook.nist.gov. Accessed 15 Apr 2015
Kazakov A, Muzny CD, Kroenlein K, Diky V, Chirico RD, Magee JW, Abdulagatov IM, Frenkel M (2012) NIST/TRC SOURCE data archival system: the next-generation data model for storage of thermophysical properties. Int J Thermophys 33(1):22–33
CAS
Google Scholar
Specs. http://www.specs.net. Accessed 19 April 2015
AKos Samples. http://www.akosgmbh.de/AKosSamples. Accessed 19 Apr 2015
ChemExper. http://www.chemexper.com. Accessed 19 Apr 2015
Guilloux V, Arrault A, Colliandre L, Bourg S, Vayer P, Morin-Allory L (2012) Mining collections of compounds with screening assistant 2. J Cheminformatics 4(1):20
Google Scholar
Masciocchi J, Frau G, Fanton M, Sturlese M, Floris M, Pireddu L, Palla P, Cedrati F, Rodriguez-Tomé P, Moro S (2009) MMsINC: a large-scale chemoinformatics database. Nucleic Acids Res 37(Suppl 1):D284–D290
CAS
Google Scholar
ChemSynthesis. http://www.chemsynthesis.com/. Accessed 19 Apr 2015
Compendium of Pesticide Common Names http://www.alanwood.net/pesticides/. Accessed 19 Apr 2015
Mol-Instincts Database based on Quantum Mechanics and QSPR. http://molinstincts.com/home/index/. Accessed 9 Apr 2015
Magoon GR, Green WH (2013) Design and implementation of a next-generation software interface for on-the-fly quantum and force field calculations in automated reaction mechanism generation. Comput Chem Eng 52:35–45
CAS
Google Scholar
Ramakrishnan R, Dral PO, Rupp M, von Lilienfeld OA (2014) Quantum chemistry structures and properties of 134 kilo molecules. Sci Data 1:140022
CAS
Google Scholar
Weber RJM, Li E, Bruty J, He S, Viant MR (2012) MaConDa: a publicly accessible mass spectrometry contaminants database. Bioinformatics 28(21):2856–2857
CAS
Google Scholar
Bruno TJ, Wolk A, Naydich A, Huber ML (2009) Composition-explicit distillation curves for mixtures of diesel fuel with dimethyl carbonate and diethyl carbonate. Energy Fuels 23(8):3989–3997
CAS
Google Scholar
Ginex T, Spyrakis F, Cozzini P (2014) FADB: a food additive molecular database for in silico screening in food toxicology. Food Addit Contam Part A 31(5):792–798
CAS
Google Scholar
Gu J, Gui Y, Chen L, Yuan G, Xu X (2013) CVDHD: a cardiovascular disease herbal database for drug discovery and network pharmacology. J Cheminformatics 5:51
Google Scholar
Kelley SP, Fabian L, Brock CP (2011) Failures of fractional crystallization: ordered co-crystals of isomers and near isomers. Acta Crystallogr B 67(1):79–93
CAS
Google Scholar
Laurence C, Brameld KA, Graton J, Le Questel J-Y, Renault E (2009) The pKBHX database: toward a better understanding of hydrogen-bond basicity for medicinal chemists. J Med Chem 52(14):4073–4086
CAS
Google Scholar
Wakelam V, Herbst E, Loison J-C, Smith IWM, Chandrasekaran V, Pavone B, Adams NG, Bacchus-Montabonel M-C, Bergeat A, Béroff K, Bierbaum VM, Chabot M, Dalgarno A, van Dishoeck EF, Faure A, Geppert WD, Gerlich D, Galli D, Hébrard E, Hersant F, Hickson KM, Honvault P, Klippenstein SJ, Le Picard S, Nyman G, Pernot P, Schlemmer S, Selsis F, Sims IR, Talbi D, Tennyson J, Troe J, Wester R, Wiesenfeld L (2012) A KInetic database for astrochemistry (KIDA). Astrophys J Suppl Ser 199(1):21
Google Scholar
Fabian L, Brock CP (2010) A list of organic kryptoracemates. Acta Crystallogr B 66(1):94–103
CAS
Google Scholar
Schenck RJ, Zapiecki KR (2014) Back to the future: CAS and the shape of chemical information to come. In: Leah RM, Buntrock RE (eds) The future of the history of chemical information, ACS symposium series, vol 1164. American Chemical Society, Washington, pp 149–158
Google Scholar
Schmidt U, Struck S, Gruening B, Hossbach J, Jaeger IS, Parol R, Lindequist U, Teuscher E, Preissner R (2009) SuperToxic: a comprehensive database of toxic compounds. Nucleic Acids Res 37(Suppl 1):D295–D299
CAS
Google Scholar
Zass E (2010) Chemical information retrieval—a short discussion about the state of the art, progress, and pitfalls. Heterocycles 82(1):63–86
CAS
Google Scholar
Zass E (2014) Looking back, but not in anger. In: McEwen LR, Buntrock RE (eds) The future of the history of chemical information, ACS symposium series, vol 1164. American Chemical Society, Washington, pp 57–80
Google Scholar
Akhondi SA, Kors JA, Muresan S (2012) Consistency of systematic chemical identifiers within and between small-molecule databases. J Cheminformatics 4:35
CAS
Google Scholar
Chambers J, Davies M, Gaulton A, Hersey A, Velankar S, Petryszak R, Hastings J, Bellis L, McGlinchey S, Overington JP (2013) UniChem: a unified chemical structure cross-referencing and identifier tracking system. J Cheminformatics 5:3
CAS
Google Scholar
Galgonek J, Vondrasek J (2014) On InChI and evaluating the quality of cross-reference links. J Cheminformatics 6:15
Google Scholar
Hilbig M, Urbaczek S, Groth I, Heuser S, Rarey M (2013) MONA—interactive manipulation of molecule collections. J Cheminformatics 5(1):38
CAS
Google Scholar
Kuhn M, Szklarczyk D, Franceschini A, Campillos M, von Mering C, Jensen LJ, Beyer A, Bork P (2010) STITCH 2: an interaction network database for small molecules and proteins. Nucleic Acids Res 38(Database issue):D552–D556
CAS
Google Scholar
Kuhn M, Szklarczyk D, Franceschini A, von Mering C, Jensen LJ, Bork P (2012) STITCH 3: zooming in on protein–chemical interactions. Nucleic Acids Res 40(D1):D876–D880
CAS
Google Scholar
Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P (2008) STITCH: interaction networks of chemicals and proteins. Nucleic Acids Res 36(Suppl 1):D684–D688
CAS
Google Scholar
Qiao Y, Wu X, Yang L, Zhang M (2007) Chemoinformatics and open source software integration and reuse. Jisuanji Yu Yingyong Huaxue 24(1):133–136
CAS
Google Scholar
Williams AJ, Ekins S, Tkachenko V (2012) Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situation. Drug Discov Today 17(13–14):685–701
CAS
Google Scholar
Orchard S, Al-Lazikani B, Bryant S, Clark D, Calder E, Dix I, Engkvist O, Forster M, Gaulton A, Gilson M, Glen R, Grigorov M, Hammond-Kosack K, Harland L, Hopkins A, Larminie C, Lynch N, Mann RK, Murray-Rust P, Lo PE, Southan C, Steinbeck C, Wishart D, Hermjakob H, Overington J, Thornton J (2011) Minimum information about a bioactive entity (MIABE). Nat Rev Drug Discov 10(9):661–669
CAS
Google Scholar
Thibault J, Roe D, Facelli J, Cheatham T (2014) Data model, dictionaries, and desiderata for biomolecular simulation data indexing and sharing. J Cheminformatics 6(1):4
Google Scholar
Thalheim T (2010) Tautomer production based on the InChI string. Nachr Chem 58(12):1253–1255
CAS
Google Scholar
Thalheim T, Vollmer A, Ebert R-U, Kuhne R, Schuurmann G (2010) Tautomer identification and tautomer structure generation based on the InChI code. J Chem Inf Model 50(7):1223–1232
CAS
Google Scholar