AIMC Topic: Gene Expression

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Hybrid wavelet-gene expression programming and wavelet-support vector machine models for rainfall-runoff modeling.

Water science and technology : a journal of the International Association on Water Pollution Research Dec 1, 2022
It is critical to use research methods to collect and regulate surface water to provide water while avoiding damage. Following accurate runoff prediction, principled planning for optimal runoff is implemented. In recent years, there has been an incre...
Computer Simulation Gene Expression Rivers Water Movements Water Support Vector Machine
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ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.

Briefings in bioinformatics Nov 19, 2022
Breast cancer patients often have recurrence and metastasis after surgery. Predicting the risk of recurrence and metastasis for a breast cancer patient is essential for the development of precision treatment. In this study, we proposed a novel multi-...
Breast Neoplasms Eosine Yellowish-(YS) Neural Networks, Computer Gene Expression Humans Deep Learning Female
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dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using time-course single-cell gene expression data.

Briefings in bioinformatics Nov 19, 2022
Time-course single-cell RNA sequencing (scRNA-seq) data have been widely used to explore dynamic changes in gene expression of transcription factors (TFs) and their target genes. This information is useful to reconstruct cell-type-specific gene regul...
Gene Expression Profiling Sequence Analysis, RNA Deep Learning Gene Expression Single-Cell Analysis
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Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine.

Briefings in bioinformatics Sep 20, 2022
Precision medicine uses genetic, environmental and lifestyle factors to more accurately diagnose and treat disease in specific groups of patients, and it is considered one of the most promising medical efforts of our time. The use of genetics is argu...
Machine Learning Precision Medicine Genomics Artificial Intelligence Gene Expression
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GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression.

Bioinformatics (Oxford, England) Apr 28, 2022
MOTIVATION: Medical care is becoming more and more specific to patients' needs due to the increased availability of omics data. The application to these data of sophisticated machine learning models, in particular deep learning (DL), can improve the ...
Machine Learning Phenotype Gene Expression Neural Networks, Computer Gene Ontology
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GSEnet: feature extraction of gene expression data and its application to Leukemia classification.

Mathematical biosciences and engineering : MBE Mar 14, 2022
Gene expression data is highly dimensional. As disease-related genes account for only a tiny fraction, a deep learning model, namely GSEnet, is proposed to extract instructive features from gene expression data. This model consists of three modules, ...
Leukemia Neural Networks, Computer Gene Expression Humans
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A deep learning model to identify gene expression level using cobinding transcription factor signals.

Briefings in bioinformatics Jan 17, 2022
Gene expression is directly controlled by transcription factors (TFs) in a complex combination manner. It remains a challenging task to systematically infer how the cooperative binding of TFs drives gene activity. Here, we quantitatively analyzed the...
Gene Expression Gene Expression Regulation Gene Regulatory Networks Transcription Factors Deep Learning
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miRNAs expression pattern and machine learning models elucidate risk for gastric GIST.

Cancer biomarkers : section A of Disease markers Jan 1, 2022
BACKGROUND: Gatrointestinal stromal tumors (GISTs) are the main mesenchymal tumors found in the gastrointestinal system. GISTs clinical phenotypes differ significantly and their molecular basis is not yet completely known. microRNAs (miRNAs) have bee...
Gastrointestinal Stromal Tumors Stomach Neoplasms Biomarkers, Tumor MicroRNAs Gene Expression Male Machine Learning Humans Prognosis Female
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Training, Validation, and Test of Deep Learning Models for Classification of Receptor Expressions in Breast Cancers From Mammograms.

JCO precision oncology Nov 1, 2021
PURPOSE: The molecular subtype of breast cancer is an important component of establishing the appropriate treatment strategy. In clinical practice, molecular subtypes are determined by receptor expressions. In this study, we developed a model using d...
Gene Expression Models, Biological Receptor, ErbB-2 Receptors, Estrogen Datasets as Topic Deep Learning Mammography Breast Neoplasms Middle Aged Humans Female Receptors, Progesterone Aged
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Current status and future perspectives of computational studies on human-virus protein-protein interactions.

Briefings in bioinformatics Sep 2, 2021
The protein-protein interactions (PPIs) between human and viruses mediate viral infection and host immunity processes. Therefore, the study of human-virus PPIs can help us understand the principles of human-virus relationships and can thus guide the ...
Computational Biology Amino Acid Sequence Antiviral Agents Viral Proteins Host-Pathogen Interactions Protein Interaction Mapping Protein Binding Databases, Genetic Gene Expression Receptors, Virus Humans CD40 Antigens Virus Diseases Machine Learning TNF Receptor-Associated Factor 3 Viruses
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