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Databases, Genetic

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PlaNC-TE: a comprehensive knowledgebase of non-coding RNAs and transposable elements in plants.

Database : the journal of biological databases and curation
Transposable elements (TEs) play an essential role in the genetic variability of eukaryotic species. In plants, they may comprise up to 90% of the total genome. Non-coding RNAs (ncRNAs) are known to control gene expression and regulation. Although th...

Effective computational detection of piRNAs using n-gram models and support vector machine.

BMC bioinformatics
BACKGROUND: Piwi-interacting RNAs (piRNAs) are a new class of small non-coding RNAs that are known to be associated with RNA silencing. The piRNAs play an important role in protecting the genome from invasive transposons in the germline. Recent studi...

ALE: automated label extraction from GEO metadata.

BMC bioinformatics
BACKGROUND: NCBI's Gene Expression Omnibus (GEO) is a rich community resource containing millions of gene expression experiments from human, mouse, rat, and other model organisms. However, information about each experiment (metadata) is in the format...

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

Biochimica et biophysica acta. Molecular basis of disease
Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene ide...

Distinguishing three subtypes of hematopoietic cells based on gene expression profiles using a support vector machine.

Biochimica et biophysica acta. Molecular basis of disease
Hematopoiesis is a complicated process involving a series of biological sub-processes that lead to the formation of various blood components. A widely accepted model of early hematopoiesis proceeds from long-term hematopoietic stem cells (LT-HSCs) to...

Hybrid Method Based on Information Gain and Support Vector Machine for Gene Selection in Cancer Classification.

Genomics, proteomics & bioinformatics
It remains a great challenge to achieve sufficient cancer classification accuracy with the entire set of genes, due to the high dimensions, small sample size, and big noise of gene expression data. We thus proposed a hybrid gene selection method, Inf...

Construction of a 26‑feature gene support vector machine classifier for smoking and non‑smoking lung adenocarcinoma sample classification.

Molecular medicine reports
The present study aimed to identify the feature genes associated with smoking in lung adenocarcinoma (LAC) samples and explore the underlying mechanism. Three gene expression datasets of LAC samples were downloaded from the Gene Expression Omnibus da...

Decontaminating eukaryotic genome assemblies with machine learning.

BMC bioinformatics
BACKGROUND: High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few exis...

Meta-Path Methods for Prioritizing Candidate Disease miRNAs.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs (miRNAs) play critical roles in regulating gene expression at post-transcriptional levels. Numerous experimental studies indicate that alterations and dysregulations in miRNAs are associated with important complex diseases, especially cance...