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Genomics

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Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation.

Genome biology
We present MUSTACHE, a new method for multi-scale detection of chromatin loops from Hi-C and Micro-C contact maps. MUSTACHE employs scale-space theory, a technical advance in computer vision, to detect blob-shaped objects in contact maps. MUSTACHE is...

Characterizing CDK12-Mutated Prostate Cancers.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Cyclin-dependent kinase 12 (CDK12) aberrations have been reported as a biomarker of response to immunotherapy for metastatic castration-resistant prostate cancer (mCRPC). Herein, we characterize CDK12-mutated mCRPC, presenting clinical, geno...

Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BMC genomics
BACKGROUND: The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far ...

CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification.

BMC bioinformatics
BACKGROUND: Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization...

Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis.

BMC medical informatics and decision making
BACKGROUND: Breast cancer is the most prevalent and among the most deadly cancers in females. Patients with breast cancer have highly variable survival lengths, indicating a need to identify prognostic biomarkers for personalized diagnosis and treatm...

A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model.

Communications biology
The analyses of multi-omics data have revealed candidate genes for objective traits. However, they are integrated poorly, especially in non-model organisms, and they pose a great challenge for prioritizing candidate genes for follow-up experimental v...

Incomplete multi-view gene clustering with data regeneration using Shape Boltzmann Machine.

Computers in biology and medicine
Deciphering patterns in the structural and functional anatomy of genes can prove to be very helpful in understanding genetic biology and genomics. Also, the availability of the multiple omics data, along with the advent of machine learning techniques...

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Open biology
Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionall...

Frequency spectra characterization of noncoding human genomic sequences.

Genes & genomics
BACKGROUND: Noncoding sequences have been demonstrated to possess regulatory functions. Its classification is challenging because they do not show well-defined nucleotide patterns that can correlate with their biological functions. Genomic signal pro...

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

mBio
Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a m...