Convergent evolution of defensin sequence, structure and function
Defensins are a well-characterised group of small, disulphide-rich, cationic peptides that are
produced by essentially all eukaryotes and are highly diverse in their sequences and …
produced by essentially all eukaryotes and are highly diverse in their sequences and …
Recent advances in machine learning methods for predicting heat shock proteins
W Chen, P Feng, T Liu, D Jin - Current Drug Metabolism, 2019 - ingentaconnect.com
Background: As molecular chaperones, Heat Shock Proteins (HSPs) not only play key roles
in protein folding and maintaining protein stabilities, but are also linked with multiple kinds of …
in protein folding and maintaining protein stabilities, but are also linked with multiple kinds of …
Deep-AmPEP30: improve short antimicrobial peptides prediction with deep learning
Antimicrobial peptides (AMPs) are a valuable source of antimicrobial agents and a potential
solution to the multi-drug resistance problem. In particular, short-length AMPs have been …
solution to the multi-drug resistance problem. In particular, short-length AMPs have been …
[HTML][HTML] pLoc_bal-mHum: predict subcellular localization of human proteins by PseAAC and quasi-balancing training dataset
KC Chou, X Cheng, X Xiao - Genomics, 2019 - Elsevier
A cell contains numerous protein molecules. One of the fundamental goals in molecular cell
biology is to determine their subcellular locations since this information is extremely …
biology is to determine their subcellular locations since this information is extremely …
[HTML][HTML] Sequence-based predictive modeling to identify cancerlectins
Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a
wide distribution to various species. They can specially identify and exclusively bind to a …
wide distribution to various species. They can specially identify and exclusively bind to a …
RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule
By reducing amino acid alphabet, the protein complexity can be significantly simplified,
which could improve computational efficiency, decrease information redundancy and reduce …
which could improve computational efficiency, decrease information redundancy and reduce …
RaacLogo: a new sequence logo generator by using reduced amino acid clusters
L Zheng, D Liu, W Yang, L Yang… - Briefings in …, 2021 - academic.oup.com
Sequence logos give a fast and concise display in visualizing consensus sequence. Protein
exhibits greater complexity and diversity than DNA, which usually affects the graphical …
exhibits greater complexity and diversity than DNA, which usually affects the graphical …
Deep-PCL: a deep learning model for prediction of cancerlectins and non cancerlectins using optimized integrated features
Lectins are types of glycoprotein that have a wide variety of different species which play an
important part in tumor discrimination due to their meaningful binding resemblance to …
important part in tumor discrimination due to their meaningful binding resemblance to …
Fertility-GRU: identifying fertility-related proteins by incorporating deep-gated recurrent units and original position-specific scoring matrix profiles
NQK Le - Journal of proteome research, 2019 - ACS Publications
Protein function prediction is one of the well-known problems in proteome research,
attracting the attention of numerous researchers. However, the implementation of deep …
attracting the attention of numerous researchers. However, the implementation of deep …
Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks
Deep learning has been increasingly used to solve a number of problems with state-of-the-
art performance in a wide variety of fields. In biology, deep learning can be applied to …
art performance in a wide variety of fields. In biology, deep learning can be applied to …