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Bioinformatics Approach for Finding Target Protein in Infectious Disease

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Bioinformatics of Human Proteomics

Part of the book series: Translational Bioinformatics ((TRBIO,volume 3))

Abstract

With the technological advancements, biological data pertaining to various infectious organisms is getting abundant. This copiousness has been useful for developing abysmal understanding of the complex biological process which leads to the diseased condition in human race. Existing mode of treatments for such infectious diseases currently faces various challenges such as drug resistance. Thus, identification of new drug targets has become one of the major objectives of the scientific community involved in drug designing. These novel drug targets can provide effective know-how of the infectious organisms in order to develop novel therapeutic agents in order to contain the spread of the disease. Systems biology approach has been considered as one of the promising approach that can effectively lead to novel drug target identification. It provides the conceptual framework for the analysis using the amalgamation of variety of data obtained from conglomeration of advanced molecular biology techniques. In this chapter, we have elaborated the systems biology approaches which can be used for identification of novel drug targets for various infectious diseases. Apart from emphasizing systems biology leads in the area of drug target identification, we have highlighted some in silico experiments performed using these techniques for the identification of novel drug targets in infectious organisms such as P. falciparum and M. tuberculosis. This chapter might help in devising the effective systems biology strategies in order to develop hypothesis toward identification of novel drug targets.

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References

  • Agüero F, Al-Lazikani B, Aslett M, Berriman M, Buckner FS, Campbell RK, Carmona S, Carruthers IM, Chan AW, Chen F, Crowther GJ, Doyle MA, Hertz-Fowler C, Hopkins AL, McAllister G, Nwaka S, Overington JP, Pain A, Paolini GV, Pieper U, Ralph SA, Riechers A, Roos DS, Sali A, Shanmugam D, Suzuki T, Van Voorhis WC, Verlinde CL. Genomic-scale prioritization of drug targets: the TDR targets database. Nat Rev Drug Discov. 2008;7(11):900–7.

    Article  PubMed  Google Scholar 

  • Anishetty S, Pulani M, Gautam P. Mycobacterium tuberculosis through metabolic pathway analysis. Comput Biol Chem. 2005;29:368.

    Article  PubMed  CAS  Google Scholar 

  • Barabasi AL, Oltvai ZN. Network biology: understanding the cell’s functional organization. Nat Rev Genet. 2004;5:101–13.

    Article  PubMed  CAS  Google Scholar 

  • Barh D, Kumar A, Misra AN. Genomic Target Database (GTD): a database of potential targets in human pathogenic bacteria. Bioinformation. 2009;4(1):50–1.

    Article  PubMed  Google Scholar 

  • Beste DJV, Hooper T, Stewart G, et al. GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism. Genome Biol. 2007;8:R89.

    Article  PubMed  Google Scholar 

  • Bi J, Wang H, Xie J. Comparative genomics of NAD(P) biosynthesis and novel antibiotic drug targets. J Cell Physiol. 2011;226(2):331–40.

    Article  PubMed  CAS  Google Scholar 

  • Bonday ZQ, Dhanasekaran S, Rangarajan PN, Padmanaban G. Import of host delta-aminolevulinate dehydratase into the malarial parasite: identification of a new drug target. Nat Med. 2000;6:898–903.

    Article  PubMed  CAS  Google Scholar 

  • Brötz-Oesterhelt H, Sass P. Postgenomic strategies in antibacterial drug discovery. Future Microbiol. 2010;5(10):1553–79.

    Article  PubMed  Google Scholar 

  • Butcher EC, Berg EL, et al. Systems biology in drug discovery. Nat Biotechnol. 2004;22(10):1253–9.

    Article  PubMed  CAS  Google Scholar 

  • Cakmak A, Qi X, Coskun SA, Das M, Cheng E, Cicek AE, Lai N, Ozsoyoglu G, Ozsoyoglu ZM. PathCase-SB architecture and database design. BMC Syst Biol. 2011;5:188.

    Article  PubMed  Google Scholar 

  • Cascante M, Boros LG, Comin-Anduix B, de Atauri P, Centelles JJ, Lee PW. Metabolic control analysis in drug discovery and disease. Nat Biotechnol. 2002;20(3):243–9.

    Article  PubMed  CAS  Google Scholar 

  • Caspi R, Foerster H, Fulcher CA, Kaipa P, Krummenacker M, Latendresse M, Paley S, Rhee SY, Shearer AG, Tissier C, Walk TC, Zhang P, Karp PD. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 2008;36:D623–31.

    Article  PubMed  CAS  Google Scholar 

  • Chanumolu SK, Rout C, Chauhan RS. UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria. PLoS One. 2012;7(3):e32833.

    Article  PubMed  CAS  Google Scholar 

  • Chua HN, Roth FP. Discovering the targets of drugs via computational systems biology. J Biol Chem. 2011;286(27):23653–8.

    Article  PubMed  CAS  Google Scholar 

  • Cole ST. Comparative mycobacterial genomics as a tool for drug target and antigen discovery. Eur Respir J Suppl. 2002;36:78s–86.

    Article  PubMed  CAS  Google Scholar 

  • Colijn C, Brandes A, Zucker J, Lun DS, Weiner B, et al. Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production. PLoS Comput Biol. 2009;5(8):e1000489.

    Article  PubMed  Google Scholar 

  • Collier N, Doan S. GENI-DB: a database of global events for epidemic intelligence. Bioinformatics. 2012;28(8):1186–8.

    Article  PubMed  CAS  Google Scholar 

  • Cornish-Bowden A, Cárdenas ML. Technological and medical implications of metabolic control analysis. Dordrecht: Kluwer Academic Publishers; 2000.

    Book  Google Scholar 

  • Diaz-Guerra E, Vernal R, Cantero W, Müllner EW, Garcia-Sanz JA. Translation controlled mRNAs: new drug targets in infectious diseases? Infect Disord Drug Targets. 2008;8(4):252–61.

    Article  PubMed  CAS  Google Scholar 

  • Drews J. Drug discovery: a historical perspective. Science. 2000;287(5460):1960–4.

    Article  PubMed  CAS  Google Scholar 

  • Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci USA. 2007;104:1777–82.

    Article  PubMed  CAS  Google Scholar 

  • Duggleby RG. The application of metabolic resistance theory to the selection of preferred target enzymes for therapeutic drugs. Comput Biomed Res. 1998;21(6):579–92.

    Article  Google Scholar 

  • Duggleby RG, Christopherson RI. Metabolic resistance to tight-binding inhibitors of enzymes involved in the de novo pyrimidine pathway, simulation of time-dependent effects. Eur J Biochem. 1984;143(1):221–6.

    Article  PubMed  CAS  Google Scholar 

  • Durot M, Bourguignon P-Y, Schachter V. Genome scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiol Rev. 2009;33(1):164–90.

    Article  PubMed  CAS  Google Scholar 

  • Edwards JS, Palsson BO. Systems properties of the Haemophilus influenzae Rd metabolic genotype. J Biol Chem. 1999;274(25):17410–16.

    Article  PubMed  CAS  Google Scholar 

  • Edwards JS, Palsson BO. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc Natl Acad Sci U S A. 2000;97(10):5528–33.

    Article  PubMed  CAS  Google Scholar 

  • Eisenthal R, Cornish-Bowden A. Prospects for antiparasitic drugs. The case of Trypanosoma brucei, the causative agent of African sleeping sickness. J Biol Chem. 1998;273(10):5500–5.

    Article  PubMed  CAS  Google Scholar 

  • Farkas IJ, Korcsmáros T, Kovács IA, Mihalik Á, Palotai R, Simkó GI, Szalay KZ, Szalay-Beko M, Vellai T, Wang S, Csermely P. Network-based tools for the identification of novel drug targets. Sci Signal. 2011;4(173):pt3.

    Article  PubMed  Google Scholar 

  • Fatumo S, Plaimas K, Mallm JP, Schramm G, Adebiyi E, Oswald M, Eils R, König R. Estimating novel potential drug targets of Plasmodium falciparum by analysing the metabolic network of knock-out strains in silico. Infect Genet Evol. 2009;9:351–8.

    Article  PubMed  CAS  Google Scholar 

  • Fauci AS. Infectious diseases: considerations for the 21st century. Clin Infect Dis. 2001;32:675–85.

    Article  PubMed  CAS  Google Scholar 

  • Feist AM, Palsson BO. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nat Biotechnol. 2008;26:659–67.

    Article  PubMed  CAS  Google Scholar 

  • Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, Karp PD, Broadbelt LJ, Hatzimanikatis V, Palsson BO. A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Boil. 2007;3:121.

    Google Scholar 

  • Fell DA. Metabolic control analysis: a survey of its theoretical and experimental development. Biochem J. 1992;286(Pt 2):313–30.

    PubMed  CAS  Google Scholar 

  • Gao Z, Li H, Zhang H, Liu X, Kang L, Luo X, Zhu W, Chen K, Wang X, Jiang H. PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics. 2008;9:104.

    Article  PubMed  Google Scholar 

  • Gutierrez-Lugo MT, Bewley CA. Susceptibility and mode of binding of the Mycobacterium tuberculosis cysteinyl transferase mycothiol ligase to tRNA synthetase inhibitors. Bioorg Med Chem Lett. 2011;21(8):2480–3.

    Article  PubMed  CAS  Google Scholar 

  • Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature. 2004;430(6995):88–93.

    Article  PubMed  CAS  Google Scholar 

  • Hecker N, Ahmed J, von Eichborn J, Dunkel M, Macha K, Eckert A, Gilson MK, Bourne PE, Preissner R. SuperTarget goes quantitative: update on drug-target interactions. Nucleic Acids Res. 2012;40:D1113–17.

    Article  PubMed  CAS  Google Scholar 

  • Heinrich R, Rapoport TA. A linear steady-state treatment of enzymatic chains. Eur J Biochem. 1974;42:89–95.

    Article  PubMed  CAS  Google Scholar 

  • Himmelreich R, Plagens H, Hilbert H, Reiner B, Herrmann R. Comparative analysis of the genomes of the bacteria Mycoplasma pneumoniae and Mycoplasma genitalium. Nucleic Acids Res. 1997;25(4):701–12.

    Article  PubMed  CAS  Google Scholar 

  • Huthmacher C, Hoppe A, Bulik S, Holzhütter HG. Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis. BMC Syst Biol. 2010;4:120.

    Article  PubMed  Google Scholar 

  • Jeong H, Mason S, Barabasi A-L, Oltvai Z. Lethality and centrality in protein networks. Nature. 2001;411:41–2.

    Article  PubMed  CAS  Google Scholar 

  • Jiang Z, Zhou Y. Using gene networks to drug target identification. J Integr Bioinformatics. 2005;2(1):14.

    Google Scholar 

  • Kacser H, Burns JA. Control of enzyme flux. Symp Soc Exp Biol. 1973;27:65–104.

    PubMed  CAS  Google Scholar 

  • Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30.

    Article  PubMed  CAS  Google Scholar 

  • Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36:D480–4.

    Article  PubMed  CAS  Google Scholar 

  • Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 2010;38:D355–60.

    Article  PubMed  CAS  Google Scholar 

  • Karp PD, Paley S, Romero P. The pathway tools software. Bioinformatics. 2002;18:S225–32.

    Article  PubMed  Google Scholar 

  • Kauffman KJ, Prakash P, Edwards JS. Advances in flux balance analysis. Curr Opin Biotechnol. 2003;14:491–6.

    Article  PubMed  CAS  Google Scholar 

  • Klipp E, Herwig R, Kowald A, Wierling C, Lehrach H. Systems biology in practice: concepts, implementation and application. Weinheim: Wiley-VCH; 2005.

    Book  Google Scholar 

  • Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS. DrugBank 3.0: a comprehensive resource for ‘omics’ research on drugs. Nucleic Acids Res. 2011;39:D1035–41.

    Article  PubMed  CAS  Google Scholar 

  • LaPorte DC, Walsh K, et al. The branch point effect. Ultrasensitivity and subsensitivity to metabolic control. J Biol Chem. 1984;259(22):14068–75.

    PubMed  CAS  Google Scholar 

  • Lee DS, Burd H, Liu J, Almaas E, Wiest O, Barabási AL, Oltvai ZN, Kapatral V. Comparative genome-scale metabolic reconstruction and flux balance analysis of multiple Staphylococcus aureus genomes identify novel antimicrobial drug targets. J Bacteriol. 2009;191(12):4015–24.

    Article  PubMed  CAS  Google Scholar 

  • Lee D-Y, Chung BKS, Yusufi FNK, Selvarasu S. In silico genome-scale modeling and analysis for identifying anti-tubercular drug targets. Drug Dev Res. 2011;72:121–9.

    Article  CAS  Google Scholar 

  • Li H, Gao Z, Kang L, Zhang H, Yang K, Kunqian Y, Luo X, Zhu W, Chen K, Shen J, Wang X, Jiang H. TarFisDock: a web server for identifying drug targets with docking approach. Nucleic Acids Res. 2006;34:W219–24.

    Article  PubMed  CAS  Google Scholar 

  • Li Z, Wang RS, Zhang XS. Two-stage flux balance analysis of metabolic networks for drug target identification. BMC Syst Biol. 2011;5(1):S11.

    Article  Google Scholar 

  • McDevitt D, Rosenberg M. Exploiting genomics to discover new antibiotics. Trends Microbiol. 2001;9(12):611–17.

    Article  PubMed  CAS  Google Scholar 

  • Mehta S, Tagore S. Functional module analysis in metabolomics: chokes. Adv Comput Res. 2009;1:1–4.

    Google Scholar 

  • Morens DM, Folkers GK, Fauci AS. The challenge of emerging and re-emerging infectious diseases. Nature. 2004;430:242–9.

    Article  PubMed  CAS  Google Scholar 

  • Oberhardt MA, Palsson BO, Papin JA. Applications of genome-scale metabolic reconstructions. Mol Syst Biol. 2009;5:320.

    Article  PubMed  Google Scholar 

  • Orth JD, Thiele I, Palsson BO. What is flux balance analysis? Nat Biotechnol. 2010;28(3):245–8.

    Article  PubMed  CAS  Google Scholar 

  • Payne DJ, Gwynn MN, Holmes DJ, Pompliano DL. Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nat Rev Drug Discov. 2007;6(1):29–40.

    Article  PubMed  CAS  Google Scholar 

  • Peterson C, Ringner M. Analyzing tumor gene expression profiles. Artif Intell Med. 2003;28:59–74.

    Article  PubMed  Google Scholar 

  • Pinney JW, Shirley MW, McConkey GA, Westhead DR. MetaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella. Nucleic Acids Res. 2005;33:1399–409.

    Article  PubMed  CAS  Google Scholar 

  • Plata G, Hsiao TL, Olszewski KL, Linás M, Vitkup D. Reconstruction and flux-balance analysis of the Plasmodium falciparum metabolic network. Mol Syst Biol. 2010;6:408.

    Article  PubMed  Google Scholar 

  • Pramanik J, Keasling JD. Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol Bioeng. 1997;56(4):398–421.

    Article  PubMed  CAS  Google Scholar 

  • Raman K, Rajagopalan P, Chandra N. Flux balance analysis of mycolic acid pathway: targets for anti-tubercular drugs. PLoS Comput Biol. 2005;1:e46.

    Article  PubMed  Google Scholar 

  • Reed JL, Vo TD, Schilling CH, Palsson BO. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol. 2003;4:R54.51–12.

    Article  Google Scholar 

  • Sakharkar KR, Sakharkar MK, Chow VT. A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa. In Silico Biol. 2004;4(3):355–60.

    PubMed  CAS  Google Scholar 

  • Sams-Dodd F. Target-based drug discovery: is something wrong? Drug Discov Today. 2005;10(2):139–47.

    Article  PubMed  CAS  Google Scholar 

  • Sarma U, Ghosh I. Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade. BMC Syst Biol. 2012a;6(1):82.

    Article  PubMed  CAS  Google Scholar 

  • Sarma U, Ghosh I. Oscillations in MAPK cascade triggered by two distinct designs of coupled positive and negative feedback loops. BMC Res Notes. 2012b;5(1):287.

    Article  PubMed  CAS  Google Scholar 

  • Sarma U, Sareen A, Maiti M, Kamat V, Sudan R, et al. Modeling and experimental analyses reveals signaling plasticity in a bi-modular assembly of CD40 receptor activated kinases. PLoS One. 2012;7(7):e39898.

    Article  PubMed  CAS  Google Scholar 

  • Schilling CH, Covert MW, Famili I, Church GM, Edwards JS, Palsson BO. Genome-scale metabolic model of Helicobacter pylori 26695. J Bacteriol. 2002;184(16):4582–93.

    Article  PubMed  CAS  Google Scholar 

  • Schomburg I, Chang A, Ebeling C, Gremse M, Heldt C, Huhn G, Schomburg D. BRENDA, the enzyme database: updates and major new developments. Nucleic Acids Res. 2004;32:D431–3.

    Article  PubMed  CAS  Google Scholar 

  • Singh V. Metabolic control analysis of biochemical pathways as an approach to in silico identification and validation of anti-tuberculosis, anti-malarial and anti-diabetic drug targets. Ph.D. thesis, University of Pune; 2009.

    Google Scholar 

  • Singh VK, Ghosh I. Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets. BMC J Theor Biol Med Model. 2006;3:27.

    Article  Google Scholar 

  • Starck J, Kallenius G, et al. Comparative proteome analysis of Mycobacterium tuberculosis grown under aerobic and anaerobic conditions. Microbiology. 2004;150:3821–9.

    Article  PubMed  CAS  Google Scholar 

  • Stark J, Callard R, Hubank M. From the top down: towards a predictive biology of signaling networks. Trends Biotechnol. 2003;21(7):290–3.

    Article  PubMed  CAS  Google Scholar 

  • Thiele I, Palsson BØ. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc. 2010;5(1):93–121.

    Article  PubMed  CAS  Google Scholar 

  • Uchiyama I, Higuchi T, Kawai M. MBGD update 2010: towards a comprehensive resource for exploring microbial genome diversity. Nucleic Acids Res. 2010;38:D361–5.

    Article  PubMed  CAS  Google Scholar 

  • Vidal M. Interactome modeling. FEBS Lett. 2005;579:1834–8.

    Article  PubMed  CAS  Google Scholar 

  • Westley AM, Westley J. Enzyme inhibition in open systems. J Biol Chem. 1996;271(10):5347.

    Article  PubMed  CAS  Google Scholar 

  • Whittaker PA. What is the relevance of bioinformatics to pharmacology? Trends Pharmacol Sci. 2003;24:434–9.

    Article  PubMed  CAS  Google Scholar 

  • WHO. Removing obstacles to healthy development. Geneva: World Health Organization; 1999.

    Google Scholar 

  • Yang IS, Ryu C, Cho KJ, Kim JK, Ong SH, Mitchell WP, Kim BS, Oh HB, Kim KH. IDBD: infectious disease biomarker database. Nucleic Acids Res. 2008;36:D455–60.

    Article  PubMed  CAS  Google Scholar 

  • Yeh I, Hanekamp T, Tsoka S, Karp PD, Altman RB. Computational analysis of Plasmodium falciparum metabolism: organizing genomic information to facilitate drug discovery. Genome Res. 2004;14(5):917–24.

    Article  PubMed  CAS  Google Scholar 

  • Yildirim MA, Goh KI, Cusick ME, Barabási AL, Vidal M. Drug-target network. Nat Biotechnol. 2007;25(10):1119–26.

    Article  PubMed  CAS  Google Scholar 

  • Zhang R, Ou HY, Zhang CT. DEG: a database of essential genes. Nucleic Acids Res. 2004;32:D271–2.

    Article  PubMed  CAS  Google Scholar 

  • Zhang D, Jia J, Meng L, Xu W, Tang L, Wang J. Synthesis and preliminary antibacterial evaluation of 2-butyl succinate-based hydroxamate derivatives containing isoxazole rings. Arch Pharm Res. 2010;33(6):831–42.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

HRK would like to thank International Center for Genetic Engineering and Biotechnology (ICGEB), New Delhi, for its support and Department of Science and Technology (DST) for providing financial support. IG acknowledges the support from DBT, Government of India, and wish to thank Dr. Vivek Singh and Mr. Ashish Singh Sisodia for sharing the unpublished data from their thesis.

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Authors and Affiliations

  1. Synthetic Biology and Biofuel Group, International Center for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

    Hemant Ritturaj Kushwaha Ph.D.

  2. School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Indira Ghosh Ph.D.

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  1. Hemant Ritturaj Kushwaha Ph.D.
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  2. Indira Ghosh Ph.D.
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Correspondence to Indira Ghosh Ph.D. .

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  1. , Medicine, Biomedical Research Center, Fudan University Zhongshan Hospital, Shang Hai, China, People's Republic

    Xiangdong Wang

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Kushwaha, H.R., Ghosh, I. (2013). Bioinformatics Approach for Finding Target Protein in Infectious Disease. In: Wang, X. (eds) Bioinformatics of Human Proteomics. Translational Bioinformatics, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5811-7_10

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