Deep learning-based advances in protein structure prediction
Obtaining an accurate description of protein structure is a fundamental step toward
understanding the underpinning of biology. Although recent advances in experimental …
understanding the underpinning of biology. Although recent advances in experimental …
[HTML][HTML] LZerD Protein-Protein Docking Webserver Enhanced With de novo Structure Prediction
C Christoffer, V Bharadwaj, R Luu… - Frontiers in molecular …, 2021 - frontiersin.org
Protein-protein docking is a useful tool for modeling the structures of protein complexes that
have yet to be experimentally determined. Understanding the structures of protein …
have yet to be experimentally determined. Understanding the structures of protein …
SPOT-Disorder2: improved protein intrinsic disorder prediction by ensembled deep learning
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to
be important in a wide range of biological functions and implicated in many diseases. Due to …
be important in a wide range of biological functions and implicated in many diseases. Due to …
Residue-wise local quality estimation for protein models from cryo-EM maps
An increasing number of protein structures are being determined by cryogenic electron
microscopy (cryo-EM). Although the resolution of determined cryo-EM density maps is …
microscopy (cryo-EM). Although the resolution of determined cryo-EM density maps is …
Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment
Protein language models have emerged as an alternative to multiple sequence alignment
for enriching sequence information and improving downstream prediction tasks such as …
for enriching sequence information and improving downstream prediction tasks such as …
SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model
Motivation Accurate prediction of protein contact-map is essential for accurate protein
structure and function prediction. As a result, many methods have been developed for …
structure and function prediction. As a result, many methods have been developed for …
Deeper profiles and cascaded recurrent and convolutional neural networks for state-of-the-art protein secondary structure prediction
Abstract Protein Secondary Structure prediction has been a central topic of research in
Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS …
Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS …
[HTML][HTML] Catabolic profiling of selective enzymes in the saccharification of non-food lignocellulose parts of biomass into functional edible sugars and bioenergy: An in …
Objectives: The research aims to analyze the catabolic strength of different hydrolytic
enzymes in assessing the biological conversion potential of lignocellulose parts of …
enzymes in assessing the biological conversion potential of lignocellulose parts of …
OPUS-TASS: a protein backbone torsion angles and secondary structure predictor based on ensemble neural networks
G Xu, Q Wang, J Ma - Bioinformatics, 2020 - academic.oup.com
Motivation Predictions of protein backbone torsion angles (ϕ and ψ) and secondary
structure from sequence are crucial subproblems in protein structure prediction. With the …
structure from sequence are crucial subproblems in protein structure prediction. With the …
SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction
Motivation Protein structures provide basic insight into how they can interact with other
proteins, their functions and biological roles in an organism. Experimental methods (eg X …
proteins, their functions and biological roles in an organism. Experimental methods (eg X …