AIMC Topic: Epistasis, Genetic
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Using machine learning and big data to explore the drug resistance landscape in HIV.
PLoS computational biology
Aug 26, 2021
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...
Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.
PloS one
Aug 26, 2021
Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to introduce the desired properties. Challenging design problems necessitate the representation of a pr...
CGINet: graph convolutional network-based model for identifying chemical-gene interaction in an integrated multi-relational graph.
BMC bioinformatics
Nov 26, 2020
BACKGROUND: Elucidation of interactive relation between chemicals and genes is of key relevance not only for discovering new drug leads in drug development but also for repositioning existing drugs to novel therapeutic targets. Recently, biological n...
Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.
Genetic epidemiology
Sep 1, 2020
Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were oft...
Molecular docking and machine learning analysis of Abemaciclib in colon cancer.
BMC molecular and cell biology
Jul 8, 2020
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...
Humans
Machine Learning
Algorithms
Gene Expression Profiling
Cell Line, Tumor
Prognosis
Molecular Docking Simulation
Benzimidazoles
Gene Expression Regulation, Neoplastic
Drug Repositioning
Fatty Acid-Binding Proteins
Epistasis, Genetic
Adenocarcinoma
Colonic Neoplasms
Neoplasm Staging
Gastrointestinal Hormones
Aminopyridines
Databases, Protein
Survival Analysis
Predicting breast cancer risk using interacting genetic and demographic factors and machine learning.
Scientific reports
Jul 6, 2020
Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially fac...
Hierarchy and levels: analysing networks to study mechanisms in molecular biology.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Feb 24, 2020
Network representations are flat while mechanisms are organized into a hierarchy of levels, suggesting that the two are fundamentally opposed. I challenge this opposition by focusing on two aspects of the ways in which large-scale networks constructe...
GenEpi: gene-based epistasis discovery using machine learning.
BMC bioinformatics
Feb 24, 2020
BACKGROUND: Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with ...
DualWMDR: Detecting epistatic interaction with dual screening and multifactor dimensionality reduction.
Human mutation
Nov 25, 2019
Detecting epistatic interaction is a typical way of identifying the genetic susceptibility of complex diseases. Multifactor dimensionality reduction (MDR) is a decent solution for epistasis detection. Existing MDR-based methods still suffer from high...
An improved fuzzy set-based multifactor dimensionality reduction for detecting epistasis.
Artificial intelligence in medicine
Nov 22, 2019
OBJECTIVE: Epistasis identification is critical for determining susceptibility to human genetic diseases. The rapid development of technology has enabled scalability to make multifactor dimensionality reduction (MDR) measurements an effective calcula...
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