AIMC Topic: Gene Expression Profiling
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Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.
Molecular cancer
Aug 28, 2021
BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells...
Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.
mSphere
Aug 25, 2021
antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investiga...
A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.
Scientific reports
Aug 19, 2021
Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplat...
Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.
BMC cancer
Aug 9, 2021
BACKGROUND: A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study was to ident...
Semi-Supervised Topological Analysis for Elucidating Hidden Structures in High-Dimensional Transcriptome Datasets.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 6, 2021
Topological data analysis (TDA) is a powerful method for reducing data dimensionality, mining underlying data relationships, and intuitively representing the data structure. The Mapper algorithm is one such tool that projects high-dimensional data to...
Discriminant Projection Shared Dictionary Learning for Classification of Tumors Using Gene Expression Data.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 6, 2021
With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as accurately as possible. The development of DNA microarrays provides an opportunity to predict tumor classification. One strategy is to use gene expre...
Correntropy-Based Hypergraph Regularized NMF for Clustering and Feature Selection on Multi-Cancer Integrated Data.
IEEE transactions on cybernetics
Aug 4, 2021
Non-negative matrix factorization (NMF) has become one of the most powerful methods for clustering and feature selection. However, the performance of the traditional NMF method severely degrades when the data contain noises and outliers or the manifo...
Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.
Scientific reports
Jul 23, 2021
COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high thr...
The impact of site-specific digital histology signatures on deep learning model accuracy and bias.
Nature communications
Jul 20, 2021
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and dri...
Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.
Scientific reports
Jul 19, 2021
For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is h...
Breast Neoplasms
Biomarkers, Tumor
Gene Expression Profiling
Transcriptome
Gene Regulatory Networks
Gene Expression Regulation, Neoplastic
Predictive Value of Tests
Mastectomy
Artificial Intelligence
Machine Learning
Chemotherapy, Adjuvant
Prognosis
Humans
Female
Neoplasm Recurrence, Local
Neural Networks, Computer
Survival Analysis
Microarray Analysis
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