AI Medical Compendium Journal:
BMC systems biology

Showing 11 to 20 of 34 articles

Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

BMC systems biology
BACKGROUND: Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, mos...

Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism.

BMC systems biology
BACKGROUND: Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive infor...

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

BMC systems biology
BACKGROUND: Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions....

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.

BMC systems biology
BACKGROUND: Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applicatio...

Reconstructing cancer drug response networks using multitask learning.

BMC systems biology
BACKGROUND: Translating in vitro results to clinical tests is a major challenge in systems biology. Here we present a new Multi-Task learning framework which integrates thousands of cell line expression experiments to reconstruct drug specific respon...

Mimvec: a deep learning approach for analyzing the human phenome.

BMC systems biology
BACKGROUND: The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using th...

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

BMC systems biology
BACKGROUND: High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets deri...

Prior knowledge guided active modules identification: an integrated multi-objective approach.

BMC systems biology
BACKGROUND: Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or diseas...

An improved method for functional similarity analysis of genes based on Gene Ontology.

BMC systems biology
BACKGROUND: Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional...

Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.

BMC systems biology
BACKGROUND: Protein-protein interactions (PPIs) are essential to most biological processes. Since bioscience has entered into the era of genome and proteome, there is a growing demand for the knowledge about PPI network. High-throughput biological te...