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Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.

BioMed research international
Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference ...

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still ...

Machine learning identifies a compact gene set for monitoring the circadian clock in human blood.

Genome medicine
BACKGROUND: The circadian clock and the daily rhythms it produces are crucial for human health, but are often disrupted by the modern environment. At the same time, circadian rhythms may influence the efficacy and toxicity of therapeutics and the met...

Character-level neural network for biomedical named entity recognition.

Journal of biomedical informatics
Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large a...

A statistical framework for biomedical literature mining.

Statistics in medicine
In systems biology, it is of great interest to identify new genes that were not previously reported to be associated with biological pathways related to various functions and diseases. Identification of these new pathway-modulating genes does not onl...

Chemical-gene relation extraction using recursive neural network.

Database : the journal of biological databases and curation
In this article, we describe our system for the CHEMPROT task of the BioCreative VI challenge. Although considerable research on the named entity recognition of genes and drugs has been conducted, there is limited research on extracting relationships...

Multi-Factored Gene-Gene Proximity Measures Exploiting Biological Knowledge Extracted from Gene Ontology: Application in Gene Clustering.

IEEE/ACM transactions on computational biology and bioinformatics
To describe the cellular functions of proteins and genes, a potential dynamic vocabulary is Gene Ontology (GO), which comprises of three sub-ontologies namely, Biological-process, Cellular-component, and Molecular-function. It has several application...

C-PUGP: A cluster-based positive unlabeled learning method for disease gene prediction and prioritization.

Computational biology and chemistry
Disease gene detection is an important stage in the understanding disease processes and treatment. Some candidate disease genes are identified using many machine learning methods Although there are some differences in these methods including feature ...

NMFGO: Gene Function Prediction via Nonnegative Matrix Factorization with Gene Ontology.

IEEE/ACM transactions on computational biology and bioinformatics
Gene Ontology (GO) is a controlled vocabulary of terms that describe molecule function, biological roles, and cellular locations of gene products (i.e., proteins and RNAs), it hierarchically organizes more than 43,000 GO terms via the direct acyclic ...

Universal method for robust detection of circadian state from gene expression.

Proceedings of the National Academy of Sciences of the United States of America
Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly imp...