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Subcategories: Genetics

Showing 3760-3780 of 10,506 articles

Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen.

Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs) such as polycythemi...

Feb 2021 PMID: 33564094

A Correlation Analysis between SNPs and ROIs of Alzheimer's Disease Based on Deep Learning.

. At present, the research methods for image genetics of Alzheimer's disease based on machine learni...

Feb 2021 PMID: 33628827

Genomic sequence analysis of lung infections using artificial intelligence technique.

Attributable to the modernization of Artificial Intelligence (AI) procedures in healthcare services,...

Feb 2021 PMID: 33558984

A machine learning method based on the genetic and world competitive contests algorithms for selecting genes or features in biological applications.

Gene/feature selection is an essential preprocessing step for creating models using machine learning...

Feb 2021 PMID: 33558580

A novel gene selection method for gene expression data for the task of cancer type classification.

Cancer is a poligenetic disease with each cancer type having a different mutation profile. Genomic d...

Feb 2021 PMID: 33557857

In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and t...

Feb 2021 PMID: 33554306

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.

The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diag...

Feb 2021 PMID: 33601166

Computational approach for identification, characterization, three-dimensional structure modelling and machine learning-based thermostability prediction of xylanases from the genome of Aspergillus fumigatus.

Identification of thermostable and alkaline xylanases from different fungal and bacterial species ha...

Feb 2021 PMID: 33601238

Optimizing ANFIS using simulated annealing algorithm for classification of microarray gene expression cancer data.

In the medical field, successful classification of microarray gene expression data is of major impor...

Feb 2021 PMID: 33543413

PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses.

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severi...

Feb 2021 PMID: 33547380

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that ma...

Feb 2021 PMID: 33547335

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has l...

Feb 2021 PMID: 33547334

Creating artificial human genomes using generative neural networks.

Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements ...

Feb 2021 PMID: 33539374

Integrating Multi-Omic Data With Deep Subspace Fusion Clustering for Cancer Subtype Prediction.

One type of cancer usually consists of several subtypes with distinct clinical implications, thus th...

Feb 2021 PMID: 31689204

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiati...

Feb 2021 PMID: 31581092

An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning.

Knowing the transcription factor binding sites (TFBSs) is essential for modeling the underlying bind...

Feb 2021 PMID: 30835229

Browse Categories

Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen.

A Correlation Analysis between SNPs and ROIs of Alzheimer's Disease Based on Deep Learning.

Genomic sequence analysis of lung infections using artificial intelligence technique.

A machine learning method based on the genetic and world competitive contests algorithms for selecting genes or features in biological applications.

A novel gene selection method for gene expression data for the task of cancer type classification.

In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.

Computational approach for identification, characterization, three-dimensional structure modelling and machine learning-based thermostability prediction of xylanases from the genome of Aspergillus fumigatus.

Optimizing ANFIS using simulated annealing algorithm for classification of microarray gene expression cancer data.

PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses.

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

Creating artificial human genomes using generative neural networks.

Integrating Multi-Omic Data With Deep Subspace Fusion Clustering for Cancer Subtype Prediction.

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning.

Robust principal component analysis-based prediction of protein-protein interaction hot spots.

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks.

ES-ARCNN: Predicting enhancer strength by using data augmentation and residual convolutional neural network.

Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.

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