Wearable flexible electronics based cardiac electrode for researcher mental stress detection system using machine learning models on single lead electrocardiogram …
In the modern world, wearable smart devices are continuously used to monitor people's
health. This study aims to develop an automatic mental stress detection system for …
health. This study aims to develop an automatic mental stress detection system for …
Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes
As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine
(6 mA), plays an essential role in various cellular processes and disease pathogenesis …
(6 mA), plays an essential role in various cellular processes and disease pathogenesis …
Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings
H Zulfiqar, Z Guo, RM Ahmad, Z Ahmed, P Cai… - Frontiers in …, 2024 - frontiersin.org
Snake venom contains many toxic proteins that can destroy the circulatory system or
nervous system of prey. Studies have found that these snake venom proteins have the …
nervous system of prey. Studies have found that these snake venom proteins have the …
A statistical analysis of the sequence and structure of thermophilic and non-thermophilic proteins
Z Ahmed, H Zulfiqar, L Tang, H Lin - International Journal of Molecular …, 2022 - mdpi.com
Thermophilic proteins have various practical applications in theoretical research and in
industry. In recent years, the demand for thermophilic proteins on an industrial scale has …
industry. In recent years, the demand for thermophilic proteins on an industrial scale has …
[HTML][HTML] Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods
H Zulfiqar, Z Guo, BK Grace-Mercure, ZY Zhang… - Computational and …, 2023 - Elsevier
Hormone binding proteins (HBPs) belong to the group of soluble carrier proteins. These
proteins selectively and non-covalently interact with hormones and promote growth …
proteins selectively and non-covalently interact with hormones and promote growth …
iThermo: a sequence-based model for identifying thermophilic proteins using a multi-feature fusion strategy
Thermophilic proteins have important application value in biotechnology and industrial
processes. The correct identification of thermophilic proteins provides important information …
processes. The correct identification of thermophilic proteins provides important information …
Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique
4mC is a type of DNA alteration that has the ability to synchronize multiple biological
movements, for example, DNA replication, gene expressions, and transcriptional …
movements, for example, DNA replication, gene expressions, and transcriptional …
MuLan-Methyl—multiple transformer-based language models for accurate DNA methylation prediction
Transformer-based language models are successfully used to address massive text-related
tasks. DNA methylation is an important epigenetic mechanism, and its analysis provides …
tasks. DNA methylation is an important epigenetic mechanism, and its analysis provides …
Meta-2OM: a multi-classifier meta-model for the accurate prediction of RNA 2′-O-methylation sites in human RNA
M Harun-Or-Roshid, NT Pham, B Manavalan… - PloS One, 2024 - journals.plos.org
2′-O-methylation (2-OM or Nm) is a widespread RNA modification observed in various
RNA types like tRNA, mRNA, rRNA, miRNA, piRNA, and snRNA, which plays a crucial role …
RNA types like tRNA, mRNA, rRNA, miRNA, piRNA, and snRNA, which plays a crucial role …
[HTML][HTML] Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins
Thermophilic proteins (TPPs) are critical for basic research and in the food industry due to
their ability to maintain a thermodynamically stable fold at extremely high temperatures …
their ability to maintain a thermodynamically stable fold at extremely high temperatures …