AIMC Topic: Databases, Genetic

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Evaluating Computational Gene Ontology Annotations.

Methods in molecular biology (Clifton, N.J.)
Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computati...

How Does the Scientific Community Contribute to Gene Ontology?

Methods in molecular biology (Clifton, N.J.)
Collaborations between the scientific community and members of the Gene Ontology (GO) Consortium have led to an increase in the number and specificity of GO terms, as well as increasing the number of GO annotations. A variety of approaches have been ...

Text Mining to Support Gene Ontology Curation and Vice Versa.

Methods in molecular biology (Clifton, N.J.)
In this chapter, we explain how text mining can support the curation of molecular biology databases dealing with protein functions. We also show how curated data can play a disruptive role in the developments of text mining methods. We review a decad...

Primer on the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essent...

The Gene Ontology and the Meaning of Biological Function.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) provides a framework and set of concepts for describing the functions of gene products from all organisms. It is specifically designed for supporting the computational representation of biological systems. A GO annotation is an...

Using the Gene Ontology to Annotate Key Players in Parkinson's Disease.

Neuroinformatics
The Gene Ontology (GO) is widely recognised as the gold standard bioinformatics resource for summarizing functional knowledge of gene products in a consistent and computable, information-rich language. GO describes cellular and organismal processes a...

Ontology-Based Prediction and Prioritization of Gene Functional Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Genes and their protein products are essential molecular units of a living organism. The knowledge of their functions is key for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and ...

Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There ar...

Introducing Machine Learning Concepts with WEKA.

Methods in molecular biology (Clifton, N.J.)
This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple da...