Abstract
Leukemia is a hematologic cancer which develops in blood tissue and causes rapid generation of immature and abnormal-shaped white blood cells. It is one of the most prominent causes of death in both men and women for which there is currently not an effective treatment. For this reason, several therapeutical strategies to determine potentially relevant genetic factors are currently under development, as targeted therapies promise to be both more effective and less toxic than current chemotherapy. In this paper, we present a network community cluster-based analysis for the identification of potential gene drug targets for acute lymphoblastic leukemia and acute myeloid leukemia.
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Bazaga, A., Vellido, A. (2020). Network Community Cluster-Based Analysis for the Identification of Potential Leukemia Drug Targets. In: Vellido, A., Gibert, K., Angulo, C., Martín Guerrero, J. (eds) Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization. WSOM 2019. Advances in Intelligent Systems and Computing, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-030-19642-4_31
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DOI: https://doi.org/10.1007/978-3-030-19642-4_31
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