AIMC Topic: Genome

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EMBL's European Bioinformatics Institute (EMBL-EBI) in 2022.

Nucleic acids research
The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the Europe...

Defining the extent of gene function using ROC curvature.

Bioinformatics (Oxford, England)
MOTIVATION: Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specif...

Deciphering signatures of natural selection via deep learning.

Briefings in bioinformatics
Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning...

DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate annotation of different genomic signals and regions (GSRs) from DNA sequences is fundamentally important for understanding gene structure, regulation and function. Numerous efforts have been made to develop machine learning-based...

transferGWAS: GWAS of images using deep transfer learning.

Bioinformatics (Oxford, England)
MOTIVATION: Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide ...

AutoDC: an automatic machine learning framework for disease classification.

Bioinformatics (Oxford, England)
MOTIVATION: The emergence of next-generation sequencing techniques opens up tremendous opportunities for researchers to uncover the basic mechanisms of disease at the molecular level. Recently, automatic machine learning (AutoML) frameworks have been...

A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling.

Methods in molecular biology (Clifton, N.J.)
Complex, distributed, and dynamic sets of clinical biomedical data are collectively referred to as multimodal clinical data. In order to accommodate the volume and heterogeneity of such diverse data types and aid in their interpretation when they are...

Genome-Enabled Prediction Methods Based on Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Growth of artificial intelligence and machine learning (ML) methodology has been explosive in recent years. In this class of procedures, computers get knowledge from sets of experiences and provide forecasts or classification. In genome-wide based pr...

AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.

Briefings in bioinformatics
With advancements in genomics, there has been substantial reduction in the cost and time of genome sequencing and has resulted in lot of data in genome databases. Antimicrobial host defense proteins provide protection against invading microbes. But c...

Varmole: a biologically drop-connect deep neural network model for prioritizing disease risk variants and genes.

Bioinformatics (Oxford, England)
SUMMARY: Population studies such as genome-wide association study have identified a variety of genomic variants associated with human diseases. To further understand potential mechanisms of disease variants, recent statistical methods associate funct...