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Gene Expression Regulation, Neoplastic

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Employing decomposable partially observable Markov decision processes to control gene regulatory networks.

Artificial intelligence in medicine
OBJECTIVE: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).

Integrated gene expression profiling and chromatin immunoprecipitation followed by sequencing: Analysis of the C-terminal binding protein in breast cancer.

The journal of obstetrics and gynaecology research
AIM: This study explored the possible mechanisms of the transcriptional regulatory activities of C-terminal binding protein (CtBP) and the role of CtBP in the pathogenesis of breast cancer.

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...

Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

PloS one
This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection su...

The method for breast cancer grade prediction and pathway analysis based on improved multiple kernel learning.

Journal of bioinformatics and computational biology
Breast cancer histologic grade represents the morphological assessment of the tumor's malignancy and aggressiveness, which is vital in clinically planning treatment and estimating prognosis for patients. Therefore, the prediction of breast cancer gra...

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles.

BioMed research international
. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous chall...

Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.

PloS one
Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent ...