Genetics

Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.

BACKGROUND: The circadian system is responsible for regulating various physiological activities and ...

Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species.

DNA N6-methyladenine (6mA) is a key DNA modification, which plays versatile roles in the cellular pr...

MTS-Stega: Linguistic Steganography Based on Multi-Time-Step.

Generative linguistic steganography encodes candidate words with conditional probability when genera...

Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology.

Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost a...

DeepBtoD: Improved RNA-binding proteins prediction via integrated deep learning.

RNA-binding proteins (RBPs) have crucial roles in various cellular processes such as alternative spl...

Artificial intelligence to identify genetic alterations in conventional histopathology.

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues...

One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate co...

Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaning...

Machine learning models identify gene predictors of waggle dance behaviour in honeybees.

The molecular characterization of complex behaviours is a challenging task as a range of different f...

Improved Artificial Neural Network with State Order Dataset Estimation for Brain Cancer Cell Diagnosis.

Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient diag...

MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect.

Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational sca...

FCNGRU: Locating Transcription Factor Binding Sites by Combing Fully Convolutional Neural Network With Gated Recurrent Unit.

Deciphering the relationship between transcription factors (TFs) and DNA sequences is very helpful f...

Nanoscale storage encryption: data storage in synthetic DNA using a cryptosystem with a neural network.

Nucleosome positioning based on DNA sequence embedding and deep learning.

BACKGROUND: Nucleosome positioning is the precise determination of the location of nucleosomes on DN...

Towards a robust out-of-the-box neural network model for genomic data.

BACKGROUND: The accurate prediction of biological features from genomic data is paramount for precis...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic ...

Chromatin interaction-aware gene regulatory modeling with graph attention networks.

Linking distal enhancers to genes and modeling their impact on target gene expression are longstandi...

Somatic Genome Editing with the Use of AI: Big Promises but Doubled Legal Issues.

Both Artificial Intelligence ('AI') and genome editing are technologies that on their own promise to...

DNA Input Classification by a Riboregulator-Based Cell-Free Perceptron.

The ability to recognize molecular patterns is essential for the continued survival of biological or...

Modified BBO-Based Multivariate Time-Series Prediction System With Feature Subset Selection and Model Parameter Optimization.

Multivariate time-series prediction is a challenging research topic in the field of time-series anal...

Think positive: An interpretable neural network for image recognition.

The COVID-19 pandemic is an ongoing pandemic and is placing additional burden on healthcare systems ...