Genetics

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

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Spiking Neural P Systems with Extended Channel Rules.

This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neur...

Learning machine approach reveals microbial signatures of diet and sex in dog.

The characterization of the microbial population of many niches of the organism, as the gastrointest...

A data-driven approach to build a predictive model of cancer patients' disease outcome by utilizing co-expression networks.

BACKGROUND: Next Generation Sequencing (NGS) technologies have revolutionized genomics data research...

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies.

Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resist...

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adi...

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential...

Artificial intelligence powered statistical genetics in biobanks.

Large-scale, sometimes nationwide, prospective genomic cohorts biobanking rich biological specimens ...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

The conventional image segmentation techniques have a lot of issues with highest computational cost ...

Personal Health Information Inference Using Machine Learning on RNA Expression Data from Patients With Cancer: Algorithm Validation Study.

BACKGROUND: As the need for sharing genomic data grows, privacy issues and concerns, such as the eth...

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation.

Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer origin, occurs...

Enhancing the interpretability of transcription factor binding site prediction using attention mechanism.

Transcription factors (TFs) regulate the gene expression of their target genes by binding to the reg...

Design of Festival Sentiment Classifier Based on Social Network.

With the development of society, more and more attention has been paid to cultural festivals. In add...

Sequencing enabling design and learning in synthetic biology.

The ability to read and quantify nucleic acids such as DNA and RNA using sequencing technologies has...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. ...

autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences.

Deep learning has proven to be a powerful method with applications in various fields including image...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between...

A deep learning model to predict RNA-Seq expression of tumours from whole slide images.

Deep learning methods for digital pathology analysis are an effective way to address multiple clinic...

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data.

BACKGROUND: Deep learning has emerged as a versatile approach for predicting complex biological phen...

An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning.

Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transien...

Prediction and analysis of prokaryotic promoters based on sequence features.

Promoter recognition is an important part of functional genomic annotation but a difficult problem. ...

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