Clinical cancer research : an official journal of the American Association for Cancer Research
Oct 5, 2017
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...
Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. Many prediction methods face limitations in learning from the high-dimensional profiles generated ...
Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in r...
Computer methods and programs in biomedicine
Aug 30, 2017
BACKGROUND AND OBJECTIVES: We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (explor...
Otolaryngologic clinics of North America
May 17, 2017
Precision medicine is the application of genotypic and Omics biomarkers to determine the most appropriate, outcome-driven therapy for individual patients. To determine the best choice of therapy, institutions use significant information technology-en...
Whereas genomes can be rapidly sequenced, the functions of many genes are incompletely or erroneously annotated because of a lack of experimental evidence or prior functional knowledge in sequence databases. To address this weakness, we describe here...
BACKGROUND: Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristic...
Gene dependency networks often undergo changes in response to different conditions. Understanding how these networks change across two conditions is an important task in genomics research. Most previous differential network analysis approaches assume...
Unsupervised data mining capable of extracting a wide range of knowledge from big data without prior knowledge or particular models is a timely application in the era of big sequence data accumulation in genome research. By handling oligonucleotide c...
BACKGROUND: The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enabl...