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pro vyhledávání: '"Rama Kaalia"'
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S10, Pp 1-15 (2022)
Abstract Background Cancers are genetically heterogeneous, so anticancer drugs show varying degrees of effectiveness on patients due to their differing genetic profiles. Knowing patient’s responses to numerous cancer drugs are needed for personaliz
Externí odkaz:
https://doaj.org/article/8b790a74b5764e87985dbd09d798f78c
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Multi-omics data are increasingly being gathered for investigations of complex diseases such as cancer. However, high dimensionality, small sample size, and heterogeneity of different omics types pose huge challenges to integrated analysis.
Externí odkaz:
https://doaj.org/article/60e59149d414458bb3a97d473f28e7cc
Autor:
Rama Kaalia, Jagath C. Rajapakse
Publikováno v:
BMC Genomics, Vol 20, Iss S9, Pp 1-14 (2019)
Abstract Background Module detection algorithms relying on modularity maximization suffer from an inherent resolution limit that hinders detection of small topological modules, especially in molecular networks where most biological processes are beli
Externí odkaz:
https://doaj.org/article/83b8153741cb45fba2749823e52deea9
Publikováno v:
BMC Genomics, Vol 20, Iss S9, Pp 1-10 (2019)
Abstract Background Semantic similarity between Gene Ontology (GO) terms is a fundamental measure for many bioinformatics applications, such as determining functional similarity between genes or proteins. Most previous research exploited information
Externí odkaz:
https://doaj.org/article/67dbb8da7ca54e86bbac623fa7020b32
Autor:
Rama Kaalia, Jagath C. Rajapakse
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S13, Pp 125-138 (2019)
Abstract Background Functional modules in protein-protein interaction networks (PPIN) are defined by maximal sets of functionally associated proteins and are vital to understanding cellular mechanisms and identifying disease associated proteins. Topo
Externí odkaz:
https://doaj.org/article/8e208748b34f4e0882b03ba5bbd4b8de
Publikováno v:
SAR and QSAR in Environmental Research. 29:1-19
Health care systems have benefitted from rational drug discovery processes like vHTS, virtual high throughput screening pharmacophores and quantitative structure-activity relationships, and many challenges have been explored using such techniques: de
Autor:
Jagath C. Rajapakse, Rama Kaalia
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 19, Iss S13, Pp 125-138 (2019)
BMC Bioinformatics, Vol 19, Iss S13, Pp 125-138 (2019)
Background Functional modules in protein-protein interaction networks (PPIN) are defined by maximal sets of functionally associated proteins and are vital to understanding cellular mechanisms and identifying disease associated proteins. Topological m
Autor:
Indira Ghosh, Rama Kaalia
Publikováno v:
Journal of Biomedical Informatics. 62:125-135
Display Omitted Semantics based approach is proposed to integrate disease associated information.DAO (Disease Association Ontology) developed to provide standards for integration.Different functional associations of disease genes included.Automatic l
Publikováno v:
Machine Learning. 103:309-341
De novo design of drugs uses the three-dimensional structure of a target protein (often called the receptor) to design molecules (or ligands) that could bind to the receptor and hence inhibit its functioning. Thus, unlike a ligand-based approach, thi
Publikováno v:
Molecular Informatics. 34:380-393
For past few decades, key objectives of rational drug discovery have been the designing of specific and selective ligands for target proteins. Infectious diseases like malaria are continuously becoming resistant to traditional medicines, which inculc