Results 111 to 120 of about 4,214,030 (374)
Measuring Cellular Biomass Composition for Computational Biology Applications
, 2018 Computational representations of metabolism are increasingly common in medical, environmental, and bioprocess applications. Cellular growth is often an important output of computational biology analyses, and therefore, accurate measurement of biomass ...
A. E. Beck, K. A. Hunt, R. Carlson
semanticscholar +1 more source
Graphics processing units in bioinformatics, computational biology and systems biology
Briefings Bioinform., 2016 Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in ...
Marco S. Nobile +3 more
semanticscholar +1 more source
Transcriptome‐wide analysis of circRNA and RBP profiles and their molecular relevance for GBM
Molecular Oncology, EarlyView.CircRNAs are differentially expressed in glioblastoma primary tumors and might serve as therapeutic targets and diagnostic markers. The investigation of circRNA and RNA‐binding proteins (RBPs) interactions shows that distinct RBPs play a role in circRNA biogenesis and function.
Julia Latowska‐Łysiak +14 more
wiley +1 more source
Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma
Molecular Oncology, EarlyView.This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu +15 more
wiley +1 more source
Computer algebra in systems biology [PDF]
arXiv, 2007 Systems biology focuses on the study of entire biological systems rather than on their individual components. With the emergence of high-throughput data generation technologies for molecular biology and the development of advanced mathematical modeling techniques, this field promises to provide important new insights.
arxiv
Correction: Suppressed Expression of T-Box Transcription Factors Is Involved in Senescence in Chronic Obstructive Pulmonary Disease. [PDF]
PLoS Computational Biology, 2017 [This corrects the article DOI: 10.1371/journal.pcbi.1002597.].
PLOS Computational Biology Staff
doaj +1 more source
Computational biology: deep learning
Emerging Topics in Life Sciences, 2017 Deep learning is the trendiest tool in a computational biologist's toolbox. This exciting class of methods, based on artificial neural networks, quickly became popular due to its competitive performance in prediction problems.
William M. Jones +3 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley +1 more source
Molecular Oncology, EarlyView.Chronic TGF‐β exposure drives epithelial HCC cells from a senescent state to a TGF‐β resistant mesenchymal phenotype. This transition is characterized by the loss of Smad3‐mediated signaling, escape from senescence, enhanced invasiveness and metastatic potential, and upregulation of key resistance modulators such as MARK1 and GRM8, ultimately promoting
Minenur Kalyoncu +11 more
wiley +1 more source
Kernel methods in genomics and computational biology [PDF]
arXiv, 2005 Support vector machines and kernel methods are increasingly popular in genomics and computational biology, due to their good performance in real-world applications and strong modularity that makes them suitable to a wide range of problems, from the classification of tumors to the automatic annotation of proteins. Their ability to work in high dimension,
arxiv