Latest AI and machine learning research in genetics for healthcare professionals.
Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability methods, such as attribution methods, can be employed to identify motif-like representations along a given...
The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fine shape details from confocal microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and pati...
BACKGROUND: Long noncoding RNAs (lncRNAs) play an important role in regulating biological activities and their prediction is significant for exploring...
The complex nature of wastewater treatment has led to search for alternative strategies such as different artificial intelligence (AI) techniques to m...
Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitiv...
The coronavirus disease 2019 (COVID-19) has swept all over the world. Due to the limited detection facilities, especially in developing countries, a l...
Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is ...
The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR r...
The reverse transcriptase polymerase chain reaction (RT-PCR) is still the routinely used test for the diagnosis of SARS-CoV-2 (COVID-19). However, acc...
This paper introduces a new hybrid approach (DBH) for solving gene selection problem that incorporates the strengths of two existing metaheuristics: b...
BACKGROUND: Cis-regulatory elements (CREs) are DNA sequence segments that regulate gene expression. Among CREs are promoters, enhancers, Boundary Elem...
An adaptive genetic algorithm based on collision detection (AGACD) is proposed to solve the problems of the basic genetic algorithm in the field of pa...
Poly (ADP-ribose) polymerase-1 (PARP1) inhibition strategy for cancer treatment is gaining advantage particularly in patients having a mutation in BRC...
BACKGROUND AND OBJECTIVE: High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, ...
Residue co-evolution has become the primary principle for estimating inter-residue distances of a protein, which are crucially important for predictin...
Recent advances in machine learning promise to yield novel insights by interrogation of large datasets ranging from gene expression and mutation data ...
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular traje...
A real-time COVID-19 detection system is an utmost requirement of the present situation. This article presents a chest X-ray image-based automated COV...
Deep generative models, such as variational autoencoders (VAEs) or deep Boltzmann machines (DBMs), can generate an arbitrary number of synthetic obser...
This short article describes the method of digital cytopathology using Z-stack scanning with or without extended focusing. This technology is suitable...