Integrative approaches for finding modular structure in biological networks

K Mitra, AR Carvunis, SK Ramesh, T Ideker - Nature Reviews Genetics, 2013 - nature.com
A central goal of systems biology is to elucidate the structural and functional architecture of
the cell. To this end, large and complex networks of molecular interactions are being rapidly …

Recent advances in network-based methods for disease gene prediction

SK Ata, M Wu, Y Fang, L Ou-Yang… - Briefings in …, 2021 - academic.oup.com
Disease–gene association through genome-wide association study (GWAS) is an arduous
task for researchers. Investigating single nucleotide polymorphisms that correlate with …

GCN-MF: disease-gene association identification by graph convolutional networks and matrix factorization

P Han, P Yang, P Zhao, S Shang, Y Liu… - Proceedings of the 25th …, 2019 - dl.acm.org
Discovering disease-gene association is a fundamental and critical biomedical task, which
assists biologists and physicians to discover pathogenic mechanism of syndromes. With …

Positive-unlabeled learning for disease gene identification

P Yang, XL Li, JP Mei, CK Kwoh, SK Ng - Bioinformatics, 2012 - academic.oup.com
Background: Identifying disease genes from human genome is an important but challenging
task in biomedical research. Machine learning methods can be applied to discover new …

End-to-end interpretable disease–gene association prediction

Y Li, Z Guo, K Wang, X Gao… - Briefings in bioinformatics, 2023 - academic.oup.com
Identifying disease–gene associations is a fundamental and critical biomedical task towards
understanding molecular mechanisms, the diagnosis and treatment of diseases. It is time …

A comprehensive dataset of genes with a loss-of-function mutant phenotype in Arabidopsis

J Lloyd, D Meinke - Plant physiology, 2012 - academic.oup.com
Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a
curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A …

Ensemble positive unlabeled learning for disease gene identification

P Yang, X Li, HN Chua, CK Kwoh, SK Ng - PloS one, 2014 - journals.plos.org
An increasing number of genes have been experimentally confirmed in recent years as
causative genes to various human diseases. The newly available knowledge can be …

Computational approaches for prioritizing candidate disease genes based on PPI networks

W Lan, J Wang, M Li, W Peng… - Tsinghua Science and …, 2015 - ieeexplore.ieee.org
With the continuing development and improvement of genome-wide techniques, a great
number of candidate genes are discovered. How to identify the most likely disease genes …

Effects of psychological stress on innate immunity and metabolism in humans: a systematic analysis

S Priyadarshini, P Aich - 2012 - journals.plos.org
Stress is perhaps easiest to conceptualize as a process which allows an organism to
accommodate for the demands of its environment such that it can adapt to the prevailing set …

Transfer learning across ontologies for phenome–genome association prediction

R Petegrosso, S Park, TH Hwang, R Kuang - Bioinformatics, 2017 - academic.oup.com
Motivation To better predict and analyze gene associations with the collection of phenotypes
organized in a phenotype ontology, it is crucial to effectively model the hierarchical structure …