AIMC Topic: Gene Expression Profiling

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Machine learning application identifies novel gene signatures from transcriptomic data of spontaneous canine hemangiosarcoma.

Briefings in bioinformatics
Angiosarcomas are soft-tissue sarcomas that form malignant vascular tissues. Angiosarcomas are very rare, and due to their aggressive behavior and high metastatic propensity, they have poor clinical outcomes. Hemangiosarcomas commonly occur in domest...

Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches.

Briefings in bioinformatics
The multi-omics molecular characterization of cancer opened a new horizon for our understanding of cancer biology and therapeutic strategies. However, a tumor biopsy comprises diverse types of cells limited not only to cancerous cells but also to tum...

FS-GBDT: identification multicancer-risk module via a feature selection algorithm by integrating Fisher score and GBDT.

Briefings in bioinformatics
Cancer is a highly heterogeneous disease caused by dysregulation in different cell types and tissues. However, different cancers may share common mechanisms. It is critical to identify decisive genes involved in the development and progression of can...

Integrative biomarker detection on high-dimensional gene expression data sets: a survey on prior knowledge approaches.

Briefings in bioinformatics
Gene expression data provide the expression levels of tens of thousands of genes from several hundred samples. These data are analyzed to detect biomarkers that can be of prognostic or diagnostic use. Traditionally, biomarker detection for gene expre...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports
Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-fre...

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning.

Nucleic acids research
Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their ass...

Determining Cell Death Pathway and Regulation by Enrichment Analysis.

Methods in molecular biology (Clifton, N.J.)
Bioinformatics tools and resources are valuable for the analysis of data sets focusing on programmed cell death. This chapter discusses methods for the generation of gene sets as well as enrichment analysis using publicly available databases.

Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models.

Methods in molecular biology (Clifton, N.J.)
Intrinsic and acquired drug resistance is a major challenge in cancer therapy. Synergistic drug combinations could help to overcome drug resistance. However, the number of possible drug combinations is enormous, and it is infeasible to experimentally...