Machine learning, artificial intelligence, and data science breaking into drug design and neglected diseases
J Peña‐Guerrero, PA Nguewa… - Wiley Interdisciplinary …, 2021 - Wiley Online Library
Abstract Machine learning (ML) is becoming capable of transforming biomolecular
interaction description and calculation, promising an impact on molecular and drug design …
interaction description and calculation, promising an impact on molecular and drug design …
A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information
Recently, language representation models have drawn a lot of attention in the natural
language processing field due to their remarkable results. Among them, bidirectional …
language processing field due to their remarkable results. Among them, bidirectional …
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 …
AlphaFold2-aware protein–DNA binding site prediction using graph transformer
Protein–DNA interactions play crucial roles in the biological systems, and identifying protein–
DNA binding sites is the first step for mechanistic understanding of various biological …
DNA binding sites is the first step for mechanistic understanding of various biological …
Deep learning in head and neck tumor multiomics diagnosis and analysis: review of the literature
X Wang, B Li - Frontiers in Genetics, 2021 - frontiersin.org
Head and neck tumors are the sixth most common neoplasms. Multiomics integrates
multiple dimensions of clinical, pathologic, radiological, and biological data and has the …
multiple dimensions of clinical, pathologic, radiological, and biological data and has the …
XGBoost improves classification of MGMT promoter methylation status in IDH1 wildtype glioblastoma
Approximately 96% of patients with glioblastomas (GBM) have IDH1 wildtype GBMs,
characterized by extremely poor prognosis, partly due to resistance to standard …
characterized by extremely poor prognosis, partly due to resistance to standard …
DLpTCR: an ensemble deep learning framework for predicting immunogenic peptide recognized by T cell receptor
Z Xu, M Luo, W Lin, G Xue, P Wang, X Jin… - Briefings in …, 2021 - academic.oup.com
Accurate prediction of immunogenic peptide recognized by T cell receptor (TCR) can greatly
benefit vaccine development and cancer immunotherapy. However, identifying …
benefit vaccine development and cancer immunotherapy. However, identifying …
Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection
NQK Le, W Li, Y Cao - Briefings in Bioinformatics, 2023 - academic.oup.com
Protein crystallization is crucial for biology, but the steps involved are complex and
demanding in terms of external factors and internal structure. To save on experimental costs …
demanding in terms of external factors and internal structure. To save on experimental costs …
A computational framework based on ensemble deep neural networks for essential genes identification
Essential genes contain key information of genomes that could be the key to a
comprehensive understanding of life and evolution. Because of their importance, studies of …
comprehensive understanding of life and evolution. Because of their importance, studies of …
[PDF][PDF] Survey on graph embeddings and their applications to machine learning problems on graphs
Dealing with relational data always required significant computational resources, domain
expertise and task-dependent feature engineering to incorporate structural information into a …
expertise and task-dependent feature engineering to incorporate structural information into a …