AIMC Topic: Transcriptome
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The Splicing Code Goes Deep.
Cell
Jan 24, 2019
The importance of genomic sequence context in generating transcriptome diversity through RNA splicing is independently unmasked by two studies in this issue (Jaganathan et al., 2019; Baeza-Centurion et al., 2019).
Using Drug Expression Profiles and Machine Learning Approach for Drug Repurposing.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
The cost of new drug development has been increasing, and repurposing known medications for new indications serves as an important way to hasten drug discovery. One promising approach to drug repositioning is to take advantage of machine learning (ML...
L1000FWD: fireworks visualization of drug-induced transcriptomic signatures.
Bioinformatics (Oxford, England)
Jun 15, 2018
MOTIVATION: As part of the NIH Library of Integrated Network-based Cellular Signatures program, hundreds of thousands of transcriptomic signatures were generated with the L1000 technology, profiling the response of human cell lines to over 20 000 sma...
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.
Cell
Apr 5, 2018
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovati...
Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2017
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...
FMLNCSIM: fuzzy measure-based lncRNA functional similarity calculation model.
Oncotarget
Jul 19, 2016
Accumulating experimental studies have indicated the influence of lncRNAs on various critical biological processes as well as disease development and progression. Calculating lncRNA functional similarity is of high value in inferring lncRNA functions...
What time is it? Deep learning approaches for circadian rhythms.
Bioinformatics (Oxford, England)
Jun 15, 2016
MOTIVATION: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measureme...
Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.
EBioMedicine
Nov 1, 2015
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes i...
A genetic filter for cancer classification on gene expression data.
Bio-medical materials and engineering
Jan 1, 2015
We present a new genetic filter to identify a predictive gene subset for cancer-type classification on gene expression profiles. This approach pursues to not only maximize correlation between selected genes and cancer types but also minimize inter-co...
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