Genetics

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

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Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemi...

A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

OBJECTIVE: Familial adenomatous polyposis (FAP) is one major type of inherited duodenal cancer. The ...

Determinants of Base Editing Outcomes from Target Library Analysis and Machine Learning.

Although base editors are widely used to install targeted point mutations, the factors that determin...

Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action.

Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial bu...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of materna...

Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding.

DNA-encoded small molecule libraries (DELs) have enabled discovery of novel inhibitors for many dist...

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in ca...

A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.

MOTIVATION: Alternative splicing makes significant contributions to functional diversity of transcri...

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning.

By combining metal nodes with organic linkers we can potentially synthesize millions of possible met...

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the im...

Predicting geographic location from genetic variation with deep neural networks.

Most organisms are more closely related to nearby than distant members of their species, creating sp...

Acute myeloid leukemia and artificial intelligence, algorithms and new scores.

Artificial intelligence, and more narrowly machine-learning, is beginning to expand humanity's capac...

Matrix factorization with neural network for predicting circRNA-RBP interactions.

BACKGROUND: Circular RNA (circRNA) has been extensively identified in cells and tissues, and plays c...

Homogeneous DNA-only keypad locks enable one-pot assay of multi-inputs.

Homogeneous DNA-only keypad locks were built with multi-stranded scalable junction substrates and a ...

Effects of CYP2C19*17 Genetic Polymorphisms on the Steady-State Concentration of Diazepam in Patients With Alcohol Withdrawal Syndrome.

Diazepam is one of the most widely prescribed tranquilizers for the therapy of alcohol withdrawal s...

Using Reactome to build an autophagy mechanism knowledgebase.

The 21st century has revealed much about the fundamental cellular process of autophagy. Autophagy co...

Prediction of N6-methyladenosine sites using convolution neural network model based on distributed feature representations.

N-methyladenosine (mA) is a well-studied and most common interior messenger RNA (mRNA) modification ...

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now...

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Chemical representations derived from deep learning are emerging as a powerful tool in areas such as...

CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.

BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques....

Machine learning uncovers cell identity regulator by histone code.

Conversion between cell types, e.g., by induced expression of master transcription factors, holds gr...

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