AI Medical Compendium Topic:
Genomics

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Gramene 2018: unifying comparative genomics and pathway resources for plant research.

Nucleic acids research
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,...

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Cancer genomics & proteomics
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in h...

SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning.

Proteomics
SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), an open-source tool that implements a novel framework to learn a sample-to-sample similarity measure from expression data observed for heterogenous samples, is presented here. SIMLR can be...

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects ...

Mirnovo: genome-free prediction of microRNAs from small RNA sequencing data and single-cells using decision forests.

Nucleic acids research
The discovery of microRNAs (miRNAs) remains an important problem, particularly given the growth of high-throughput sequencing, cell sorting and single cell biology. While a large number of miRNAs have already been annotated, there may well be large n...

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

GigaScience
The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses...

DOMINO: Using Machine Learning to Predict Genes Associated with Dominant Disorders.

American journal of human genetics
In contrast to recessive conditions with biallelic inheritance, identification of dominant (monoallelic) mutations for Mendelian disorders is more difficult, because of the abundance of benign heterozygous variants that act as massive background nois...

OLS Client and OLS Dialog: Open Source Tools to Annotate Public Omics Datasets.

Proteomics
The availability of user-friendly software to annotate biological datasets and experimental details is becoming essential in data management practices, both in local storage systems and in public databases. The Ontology Lookup Service (OLS, http://ww...

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Bioinformatics (Oxford, England)
MOTIVATION: Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of ...

Rectified factor networks for biclustering of omics data.

Bioinformatics (Oxford, England)
MOTIVATION: Biclustering has become a major tool for analyzing large datasets given as matrix of samples times features and has been successfully applied in life sciences and e-commerce for drug design and recommender systems, respectively. actor nal...