Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Tolerance to stress conditions is vital for organismal survival, including bacteria under specific e...

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. ...

iORI-ENST: identifying origin of replication sites based on elastic net and stacking learning.

DNA replication is not only the basis of biological inheritance but also the most fundamental proces...

Integrated multi-omics analysis of ovarian cancer using variational autoencoders.

Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., D...

Machine Learning Prediction and Experimental Validation of Antigenic Drift in H3 Influenza A Viruses in Swine.

The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development...

Action detection using a neural network elucidates the genetics of mouse grooming behavior.

Automated detection of complex animal behaviors remains a challenging problem in neuroscience, parti...

PhotoModPlus: A web server for photosynthetic protein prediction from genome neighborhood features.

A new web server called PhotoModPlus is presented as a platform for predicting photosynthetic protei...

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Deep learning methods hold strong promise for identifying biomarkers for clinical application. Howev...

Deep learning detects genetic alterations in cancer histology generated by adversarial networks.

Deep learning can detect microsatellite instability (MSI) from routine histology images in colorecta...

AptaNet as a deep learning approach for aptamer-protein interaction prediction.

Aptamers are short oligonucleotides (DNA/RNA) or peptide molecules that can selectively bind to thei...

JSOM: Jointly-evolving self-organizing maps for alignment of biological datasets and identification of related clusters.

With the rapid advances of various single-cell technologies, an increasing number of single-cell dat...

Genetic-fuzzy logic model for a non-invasive measurement of a stroke volume.

BACKGROUND: Despite the importance of stroke volume readings in understanding the work of the cardio...

A two-stream convolutional neural network for microRNA transcription start site feature integration and identification.

MicroRNAs (miRNAs) play important roles in post-transcriptional gene regulation and phenotype develo...

DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires.

Deep learning algorithms have been utilized to achieve enhanced performance in pattern-recognition t...

Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls.

Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietar...

DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.

Approximately 15% of human cancers are estimated to be attributed to viruses. Virus sequences can be...

Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning.

Elucidating functionality in non-coding regions is a key challenge in human genomics. It has been sh...

Deep learning-based enhancement of epigenomics data with AtacWorks.

ATAC-seq is a widely-applied assay used to measure genome-wide chromatin accessibility; however, its...

Development of a neuron model based on DNAzyme regulation.

Neural networks based on DNA molecular circuits play an important role in molecular information proc...

seqQscorer: automated quality control of next-generation sequencing data using machine learning.

Controlling quality of next-generation sequencing (NGS) data files is a necessary but complex task. ...

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