AIMC Topic: Transcriptome

Clear Filters Showing 481 to 490 of 899 articles

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...
Computational Biology Databases, Genetic Ovarian Neoplasms Supervised Machine Learning Computer Simulation Female Gene Expression Profiling Transcriptome Data Mining Humans Algorithms
View on PubMed DOI

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...
Neoplasms Gene Expression Profiling Transcriptome Computational Biology Databases, Genetic Humans Machine Learning Algorithms
View on PubMed DOI

Identification of Tissue of Origin and Guided Therapeutic Applications in Cancers of Unknown Primary Using Deep Learning and RNA Sequencing (TransCUPtomics).

The Journal of molecular diagnostics : JMD Jul 26, 2021
Cancers of unknown primary (CUP) are metastatic cancers for which the primary tumor is not found despite thorough diagnostic investigations. Multiple molecular assays have been proposed to identify the tissue of origin (TOO) and inform clinical care;...
Data Accuracy Neoplasms, Unknown Primary Gene Fusion Middle Aged Transcriptome Humans Deep Learning Prospective Studies RNA-Seq Retrospective Studies Adult Aged Female Biomarkers, Tumor Aged, 80 and over Male
View on PubMed DOI

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...
Neoplasm Recurrence, Local Survival Analysis Microarray Analysis Chemotherapy, Adjuvant Gene Regulatory Networks Gene Expression Regulation, Neoplastic Predictive Value of Tests Mastectomy Neural Networks, Computer Artificial Intelligence Machine Learning Prognosis Biomarkers, Tumor Gene Expression Profiling Transcriptome Female Breast Neoplasms Humans
View on PubMed DOI

Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology Jul 16, 2021
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...
Male Neoplasms Transcriptome Genome-Wide Association Study Protein Interaction Maps Humans Machine Learning Software Female Gene Expression Regulation, Developmental Transcription Factors Multigene Family Gene Regulatory Networks Genome, Human Genetic Association Studies Tissue Distribution Computational Biology Models, Genetic
View on PubMed DOI

An Unbiased Machine Learning Exploration Reveals Gene Sets Predictive of Allograft Tolerance After Kidney Transplantation.

Frontiers in immunology Jul 8, 2021
Efforts at finding potential biomarkers of tolerance after kidney transplantation have been hindered by limited sample size, as well as the complicated mechanisms underlying tolerance and the potential risk of rejection after immunosuppressant withdr...
Oligonucleotide Array Sequence Analysis Time Factors Transplantation Tolerance Risk Factors Humans Immunosuppressive Agents Graft Survival Risk Assessment Machine Learning Predictive Value of Tests Treatment Outcome Gene Expression Profiling Kidney Transplantation Graft Rejection Transcriptome Databases, Genetic Clinical Decision-Making Patient Selection
View on PubMed DOI

Dual-Organ Transcriptomic Analysis of Rainbow Trout Infected With Through Co-Expression and Machine Learning.

Frontiers in immunology Jul 8, 2021
is a major pathogen that causes a high mortality rate in trout farms. However, systemic responses to the pathogen and its interactions with multiple organs during the course of infection have not been well described. In this study, dual-organ transc...
Oncorhynchus mykiss Transcriptome Ciliophora Infections RNA-Seq Hymenostomatida Gene Regulatory Networks Virulence Immunity, Innate Machine Learning Signal Transduction Host-Pathogen Interactions Gene Expression Regulation Fish Diseases Animals Gills Liver Head Kidney Virulence Factors
View on PubMed DOI

Machine learning compensates fold-change method and highlights oxidative phosphorylation in the brain transcriptome of Alzheimer's disease.

Scientific reports Jul 1, 2021
Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the mechanism of disease development is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of AD's...
Humans Machine Learning Brain Oxidative Phosphorylation Transcriptome Alzheimer Disease
View on PubMed DOI

The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning.

Frontiers in immunology Jun 28, 2021
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies.
Aged Stomach Neoplasms Tumor Microenvironment Biomarkers, Tumor Middle Aged Transcriptome Deep Learning T-Lymphocytes Male Macrophages Prognosis Female Reproducibility of Results Humans Immunotherapy
View on PubMed DOI

Prediction of drug efficacy from transcriptional profiles with deep learning.

Nature biotechnology Jun 17, 2021
Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning-based efficacy predicti...
Deep Learning Mice Animals Proteins Drug Discovery Drug Repositioning Transcriptome
View on PubMed DOI
Popular Topics
Recent Journals