Transformer-based deep learning for predicting protein properties in the life sciences
Recent developments in deep learning, coupled with an increasing number of sequenced
proteins, have led to a breakthrough in life science applications, in particular in protein …
proteins, have led to a breakthrough in life science applications, in particular in protein …
Biological sequence classification: A review on data and general methods
C Ao, S Jiao, Y Wang, L Yu, Q Zou - Research, 2022 - spj.science.org
With the rapid development of biotechnology, the number of biological sequences has
grown exponentially. The continuous expansion of biological sequence data promotes the …
grown exponentially. The continuous expansion of biological sequence data promotes the …
Machine learning meets omics: applications and perspectives
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
Deep learning in proteomics
Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich
science. Protein sequences and structures are comprehensively catalogued in online …
science. Protein sequences and structures are comprehensively catalogued in online …
Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications
Q Zhong, X **ao, Y Qiu, Z Xu, C Chen, B Chong… - MedComm, 2023 - Wiley Online Library
Protein posttranslational modifications (PTMs) refer to the breaking or generation of covalent
bonds on the backbones or amino acid side chains of proteins and expand the diversity of …
bonds on the backbones or amino acid side chains of proteins and expand the diversity of …
GPS 6.0: an updated server for prediction of kinase-specific phosphorylation sites in proteins
M Chen, W Zhang, Y Gou, D Xu, Y Wei… - Nucleic acids …, 2023 - academic.oup.com
Protein phosphorylation, catalyzed by protein kinases (PKs), is one of the most important
post-translational modifications (PTMs), and involved in regulating almost all of biological …
post-translational modifications (PTMs), and involved in regulating almost all of biological …
Anticancer peptides prediction with deep representation learning features
Anticancer peptides constitute one of the most promising therapeutic agents for combating
common human cancers. Using wet experiments to verify whether a peptide displays …
common human cancers. Using wet experiments to verify whether a peptide displays …
Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model
Post-translational modifications (PTMs) are pivotal in modulating protein functions and
influencing cellular processes like signaling, localization, and degradation. The complexity …
influencing cellular processes like signaling, localization, and degradation. The complexity …
Applications of deep learning in understanding gene regulation
Gene regulation is a central topic in cell biology. Advances in omics technologies and the
accumulation of omics data have provided better opportunities for gene regulation studies …
accumulation of omics data have provided better opportunities for gene regulation studies …
Incorporating machine learning into established bioinformatics frameworks
N Auslander, AB Gussow, EV Koonin - International journal of molecular …, 2021 - mdpi.com
The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …
numerous machine learning techniques to address emerging problems in biology and …