AIMC Topic: Databases, Genetic

Clear Filters Showing 711 to 720 of 747 articles

Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network.

Combinatorial chemistry & high throughput screening
BACKGROUND: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big pro...

Tutorial on Protein Ontology Resources.

Methods in molecular biology (Clifton, N.J.)
The Protein Ontology (PRO) is the reference ontology for proteins in the Open Biomedical Ontologies (OBO) foundry and consists of three sub-ontologies representing protein classes of homologous genes, proteoforms (e.g., splice isoforms, sequence vari...

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...

The Vision and Challenges of the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
The overarching goal of the Gene Ontology (GO) Consortium is to provide researchers in biology and biomedicine with all current functional information concerning genes and the cellular context under which these occur. When the GO was started in the 1...

Complementary Sources of Protein Functional Information: The Far Side of GO.

Methods in molecular biology (Clifton, N.J.)
The GO captures many aspects of functional annotations, but there are other alternative complementary sources of protein function information. For example, enzyme functional annotations are described in a range of resources from the Enzyme Commission...

The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations.

Methods in molecular biology (Clifton, N.J.)
The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO des...

Annotation Extensions.

Methods in molecular biology (Clifton, N.J.)
The specificity of knowledge that Gene Ontology (GO) annotations currently can represent is still restricted by the legacy format of the GO annotation file, a format intentionally designed for simplicity to keep the barriers to entry low and thus enc...

Visualizing GO Annotations.

Methods in molecular biology (Clifton, N.J.)
Contemporary techniques in biology produce readouts for large numbers of genes simultaneously, the typical example being differential gene expression measurements. Moreover, those genes are often richly annotated using GO terms that describe gene fun...

Gene Ontology: Pitfalls, Biases, and Remedies.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its s...

Get GO! Retrieving GO Data Using AmiGO, QuickGO, API, Files, and Tools.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology Consortium (GOC) produces a wealth of resources widely used throughout the scientific community. In this chapter, we discuss the different ways in which researchers can access the resources of the GOC. We here share details about th...