Mapping gene regulatory networks from single-cell omics data
MWEJ Fiers, L Minnoye, S Aibar… - Briefings in …, 2018 - academic.oup.com
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into
cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states …
cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states …
[HTML][HTML] Network medicine in the age of biomedical big data
Network medicine is an emerging area of research dealing with molecular and genetic
interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale …
interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale …
Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities
Gene regulation plays a critical role in the cellular processes that underlie human health and
disease. The regulatory relationship between transcription factors (TFs), key regulators of …
disease. The regulatory relationship between transcription factors (TFs), key regulators of …
[HTML][HTML] Gene size matters: an analysis of gene length in the human genome
While it is expected for gene length to be associated with factors such as intron number and
evolutionary conservation, we are yet to understand the connections between gene length …
evolutionary conservation, we are yet to understand the connections between gene length …
Single-cell transcriptomic analysis of allergen-specific T cells in allergy and asthma
CD4+ T helper (TH) cells and regulatory T (Treg) cells that respond to common allergens
play an important role in driving and dampening airway inflammation in patients with …
play an important role in driving and dampening airway inflammation in patients with …
[HTML][HTML] Genome interpretation using in silico predictors of variant impact
Estimating the effects of variants found in disease driver genes opens the door to
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
[HTML][HTML] Integrative omics approaches for biosynthetic pathway discovery in plants
Covering: up to 2022 With the emergence of large amounts of omics data, computational
approaches for the identification of plant natural product biosynthetic pathways and their …
approaches for the identification of plant natural product biosynthetic pathways and their …
[HTML][HTML] Using recurrent neural networks for predicting type-2 diabetes from genomic and tabular data
The development of genomic technology for smart diagnosis and therapies for various
diseases has lately been the most demanding area for computer-aided diagnostic and …
diseases has lately been the most demanding area for computer-aided diagnostic and …
Deep learning for inferring gene relationships from single-cell expression data
Y Yuan, Z Bar-Joseph - Proceedings of the National …, 2019 - National Acad Sciences
Several methods were developed to mine gene–gene relationships from expression data.
Examples include correlation and mutual information methods for coexpression analysis …
Examples include correlation and mutual information methods for coexpression analysis …
[HTML][HTML] Artificial intelligence in drug discovery: a comprehensive review of data-driven and machine learning approaches
As expenditure on drug development increases exponentially, the overall drug discovery
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …