AIMC Topic: Transcription Factors

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Design of Knowledge Bases for Plant Gene Regulatory Networks.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary ...
Software User-Computer Interface Computational Biology Transcription Factors Databases, Genetic Gene Regulatory Networks Protein Binding Search Engine Database Management Systems Web Browser Transcription Initiation Site Chromosome Mapping Binding Sites Gene Expression Regulation, Plant Plants Knowledge Bases
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DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2017
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...
Genomics Computational Biology Models, Genetic Humans Neural Networks, Computer DNA Genome, Human Binding Sites Transcription Factors Databases, Genetic
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Genome wide predictions of miRNA regulation by transcription factors.

Bioinformatics (Oxford, England) Sep 1, 2016
MOTIVATION: Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and m...
Transcription Factors MicroRNAs Humans Machine Learning Gene Regulatory Networks RNA, Messenger Gene Expression Profiling
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ChIP-PIT: Enhancing the Analysis of ChIP-Seq Data Using Convex-Relaxed Pair-Wise Interaction Tensor Decomposition.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
In recent years, thanks to the efforts of individual scientists and research consortiums, a huge amount of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experimental data have been accumulated. Instead of investigati...
Oligonucleotide Array Sequence Analysis Chromatin Immunoprecipitation Databases, Genetic Cell Line Algorithms Reproducibility of Results Models, Theoretical Transcription Factors Computational Biology Humans Machine Learning
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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...
Mycobacterium Tuberculosis Lymphocytes Signal Transduction Transcription Factors Leukocyte Count Interferons Disease Resistance Disease Susceptibility Binding Sites Male Gene Expression Profiling Protein Binding Monocytes Transcriptome Young Adult Adult Humans Female
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Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

Journal of biosciences Oct 1, 2015
Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low predicti...
Support Vector Machine Escherichia coli Escherichia coli Proteins Saccharomyces cerevisiae Datasets as Topic Computational Biology Transcription Factors Gene Regulatory Networks Saccharomyces cerevisiae Proteins Gene Expression Regulation, Bacterial Gene Expression Regulation, Fungal
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