AIMC Topic: Gene Expression Regulation, Neoplastic
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Identifying common transcriptome signatures of cancer by interpreting deep learning models.
Genome biology
May 17, 2022
BACKGROUND: Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely bet...
Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system.
BMC bioinformatics
Apr 8, 2022
OBJECTIVES: Immune microenvironment was closely related to the occurrence and progression of colorectal cancer (CRC). The objective of the current research was to develop and verify a Machine learning survival predictive system for CRC based on immun...
Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning.
Oxidative medicine and cellular longevity
Mar 4, 2022
BACKGROUND: Ovarian cancer (OC) is a malignancy exhibiting high mortality in female tumors. Glycosylation is a posttranslational modification of proteins but research has failed to demonstrate a systematic link between glycosylation-related signature...
Machine Learning Identifies Pan-Cancer Landscape of Nrf2 Oxidative Stress Response Pathway-Related Genes.
Oxidative medicine and cellular longevity
Feb 17, 2022
BACKGROUND: Oxidative stress produced a large amount of reactive oxygen species (ROS), which played a pivotal role in balanced ability and determining cell fate. The activated Nrf2 signaling pathway that responds to the excessive ROS regulated the ex...
Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer.
Nature communications
Feb 10, 2022
Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-base...
G-protein coupled receptor-associated sorting protein 1 (GASP-1), a ubiquitous tumor marker, promotes proliferation and invasion of triple negative breast cancer.
Experimental and molecular pathology
Feb 2, 2022
We have identified the novel protein GASP-1 (G protein coupled receptor-associated sorting protein 1) that appears to be a universal cancer marker and the expression of which in tumor tissue and patient sera is predictive of cancer severity (Tuszynsk...
Deep learning identified glioblastoma subtypes based on internal genomic expression ranks.
BMC cancer
Jan 20, 2022
BACKGROUND: Glioblastoma (GBM) can be divided into subtypes according to their genomic features, including Proneural (PN), Neural (NE), Classical (CL) and Mesenchymal (ME). However, it is a difficult task to unify various genomic expression profiles ...
Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning.
Cells
Jan 15, 2022
Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discover...
Identifying Cancer Subtypes Using a Residual Graph Convolution Model on a Sample Similarity Network.
Genes
Dec 27, 2021
Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new cancer drugs, treatment from which patients would benefit most. Most previous studies detect cancer subtypes by extracting features from individual sample...
MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes.
PloS one
Dec 16, 2021
Translating in vitro results from experiments with cancer cell lines to clinical applications requires the selection of appropriate cell line models. Here we present MFmap (model fidelity map), a machine learning model to simultaneously predict the c...
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