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Transcription, Genetic

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Classifying cancer genome aberrations by their mutually exclusive effects on transcription.

BMC medical genomics
BACKGROUND: Malignant tumors are typically caused by a conglomeration of genomic aberrations-including point mutations, small insertions, small deletions, and large copy-number variations. In some cases, specific chemotherapies and targeted drug trea...

Candida albicans-derived mannoproteins activate NF-κB in reporter cells expressing TLR4, MD2 and CD14.

PloS one
The ability of soluble C. albicans 20A (serotype A) mannoprotein (CMP) to serve as a ligand for toll-like receptor 4 (TLR4) and its co-receptors was examined using commercially available and stably-transfected HEK293 cells that express human TLR4, MD...

Network stratification analysis for identifying function-specific network layers.

Molecular bioSystems
A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (Ne...

Identification of transcription factors that may reprogram lung adenocarcinoma.

Artificial intelligence in medicine
BACKGROUND: Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progre...

Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

IEEE/ACM transactions on computational biology and bioinformatics
Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes. T...

RNA-seq assistant: machine learning based methods to identify more transcriptional regulated genes.

BMC genomics
BACKGROUND: Although different quality controls have been applied at different stages of the sample preparation and data analysis to ensure both reproducibility and reliability of RNA-seq results, there are still limitations and bias on the detectabi...

Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence.

Proceedings of the National Academy of Sciences of the United States of America
Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological ...

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

Nature genetics
We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,7...

Similarity corpus on microbial transcriptional regulation.

Journal of biomedical semantics
BACKGROUND: The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the constant increase in published lit...