AIMC Topic: Genome
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Knockoff boosted tree for model-free variable selection.
Bioinformatics (Oxford, England)
May 17, 2021
MOTIVATION: The recently proposed knockoff filter is a general framework for controlling the false discovery rate (FDR) when performing variable selection. This powerful new approach generates a 'knockoff' of each variable tested for exact FDR contro...
Challenges of developing artificial intelligence-assisted tools for clinical medicine.
Journal of gastroenterology and hepatology
Feb 1, 2021
Machine learning, a subset of artificial intelligence (AI), is a set of computational tools that can be used to enhance provision of clinical care in all areas of medicine. Gastroenterology and hepatology utilize multiple sources of information, incl...
The Human Phenotype Ontology in 2021.
Nucleic acids research
Jan 8, 2021
The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for ...
Mouse Genome Database (MGD): Knowledgebase for mouse-human comparative biology.
Nucleic acids research
Jan 8, 2021
The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the community model organism knowledgebase for the laboratory mouse, a widely used animal model for comparative studies of the genetic and genomic basis for human health and disease. ...
Machine Learning to Identify Gene Interactions from High-Throughput Mutant Crosses.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2021
Advances in molecular genetics through high-throughput gene mutagenesis and genetic crossing have enabled gene interaction mapping across whole genomes. Detecting gene interactions in even small microbial genomes relies on measuring growth phenotypes...
Artificial Intelligence for Epigenetics: Towards Personalized Medicine.
Current medicinal chemistry
Jan 1, 2021
Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function, not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mec...
Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data.
Bioinformatics (Oxford, England)
Dec 30, 2020
MOTIVATION: Predictive models of DNA chromatin profile (i.e. epigenetic state), such as transcription factor binding, are essential for understanding regulatory processes and developing gene therapies. It is known that the 3D genome, or spatial struc...
Improved survival analysis by learning shared genomic information from pan-cancer data.
Bioinformatics (Oxford, England)
Jul 1, 2020
MOTIVATION: Recent advances in deep learning have offered solutions to many biomedical tasks. However, there remains a challenge in applying deep learning to survival analysis using human cancer transcriptome data. As the number of genes, the input v...
Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.
Journal of animal science
Jun 1, 2020
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populatio...
BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree.
Nucleic acids research
Jan 8, 2020
The BiGG Models knowledge base (http://bigg.ucsd.edu) is a centralized repository for high-quality genome-scale metabolic models. For the past 12 years, the website has allowed users to browse and search metabolic models. Within this update, we detai...
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