AIMC Topic: Transcriptome
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Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.
Proteins
Nov 29, 2017
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...
Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems.
PLoS computational biology
Nov 17, 2017
Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series ...
Structured Penalized Logistic Regression for Gene Selection in Gene Expression Data Analysis.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 30, 2017
In gene expression data analysis, the problems of cancer classification and gene selection are closely related. Successfully selecting informative genes will significantly improve the classification performance. To identify informative genes from a l...
Comparative Analysis of the Cytology and Transcriptomes of the Cytoplasmic Male Sterility Line H276A and Its Maintainer Line H276B of Cotton (Gossypium barbadense L.).
International journal of molecular sciences
Oct 25, 2017
In this study, the tetrad stage of microspore development in a new cotton ( L.) cytoplasmic male sterility (CMS) line, H276A, was identified using paraffin sections at the abortion stage. To explore the molecular mechanism underlying CMS in cotton, a...
Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.
Clinical cancer research : an official journal of the American Association for Cancer Research
Oct 5, 2017
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...
Integrating multiple fitting regression and Bayes decision for cancer diagnosis with transcriptomic data from tumor-educated blood platelets.
The Analyst
Aug 30, 2017
The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from ind...
Employing decomposable partially observable Markov decision processes to control gene regulatory networks.
Artificial intelligence in medicine
Jul 18, 2017
OBJECTIVE: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).
Combining Supervised and Unsupervised Learning for Improved miRNA Target Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Jul 13, 2017
MicroRNAs (miRNAs) are short non-coding RNAs which bind to mRNAs and regulate their expression. MiRNAs have been found to be associated with initiation and progression of many complex diseases. Investigating miRNAs and their targets can thus help dev...
Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.
Cell systems
Jul 12, 2017
Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, ...
Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles.
Artificial intelligence in medicine
Jun 3, 2017
OBJECTIVE: Synergistic drug combinations are promising therapies for cancer treatment. However, effective prediction of synergistic drug combinations is quite challenging as mechanisms of drug synergism are still unclear. Various features such as dru...
Antineoplastic Combined Chemotherapy Protocols
Databases, Genetic
Drug Synergism
Transcriptome
Reproducibility of Results
Humans
Gene Expression Regulation, Neoplastic
Pharmacogenetics
Neoplasms
Artificial Intelligence
Signal Transduction
Protein Interaction Maps
Computer Simulation
Gene Expression Profiling
Gene Regulatory Networks
Computational Biology
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