AI Medical Compendium Topic:
Genomics

Clear Filters Showing 631 to 640 of 952 articles

The Human Phenotype Ontology in 2017.

Nucleic acids research
Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.hum...

Semi-supervised learning for genomic prediction of novel traits with small reference populations: an application to residual feed intake in dairy cattle.

Genetics, selection, evolution : GSE
BACKGROUND: Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a s...

SGFSC: speeding the gene functional similarity calculation based on hash tables.

BMC bioinformatics
BACKGROUND: In recent years, many measures of gene functional similarity have been proposed and widely used in all kinds of essential research. These methods are mainly divided into two categories: pairwise approaches and group-wise approaches. Howev...

Symbiont modulates expression of specific gene categories in Angomonas deanei.

Memorias do Instituto Oswaldo Cruz
Trypanosomatids are parasites that cause disease in humans, animals, and plants. Most are non-pathogenic and some harbor a symbiotic bacterium. Endosymbiosis is part of the evolutionary process of vital cell functions such as respiration and photosyn...

ACID: Association Correction for Imbalanced Data in GWAS.

IEEE/ACM transactions on computational biology and bioinformatics
Genome-wide association study (GWAS) has been widely witnessed as a powerful tool for revealing suspicious loci from various diseases. However, real world GWAS tasks always suffer from the data imbalance problem of sufficient control samples and limi...

Tissue enrichment analysis for C. elegans genomics.

BMC bioinformatics
BACKGROUND: Over the last ten years, there has been explosive development in methods for measuring gene expression. These methods can identify thousands of genes altered between conditions, but understanding these datasets and forming hypotheses base...

Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

BMC systems biology
BACKGROUND: The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several c...

Extensive complementarity between gene function prediction methods.

Bioinformatics (Oxford, England)
MOTIVATION: The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct ge...

Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding.

IEEE/ACM transactions on computational biology and bioinformatics
This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to rep...

Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification-Salvinorin A as a case study.

Journal of molecular graphics & modelling
Drug abuse is a serious problem worldwide. Recently, hallucinogens have been reported as a potential preventative and auxiliary therapy for substance abuse. However, the use of hallucinogens as a drug abuse treatment has potential risks, as the funda...