[HTML][HTML] The language of proteins: NLP, machine learning & protein sequences
Natural language processing (NLP) is a field of computer science concerned with automated
text and language analysis. In recent years, following a series of breakthroughs in deep and …
text and language analysis. In recent years, following a series of breakthroughs in deep and …
A brief history of protein sorting prediction
Ever since the signal hypothesis was proposed in 1971, the exact nature of signal peptides
has been a focus point of research. The prediction of signal peptides and protein subcellular …
has been a focus point of research. The prediction of signal peptides and protein subcellular …
SignalP 6.0 predicts all five types of signal peptides using protein language models
Signal peptides (SPs) are short amino acid sequences that control protein secretion and
translocation in all living organisms. SPs can be predicted from sequence data, but existing …
translocation in all living organisms. SPs can be predicted from sequence data, but existing …
SignalP 5.0 improves signal peptide predictions using deep neural networks
JJ Almagro Armenteros, KD Tsirigos… - Nature …, 2019 - nature.com
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly
synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can …
synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can …
BUSCA: an integrative web server to predict subcellular localization of proteins
Here, we present BUSCA (http://busca. biocomp. unibo. it), a novel web server that
integrates different computational tools for predicting protein subcellular localization …
integrates different computational tools for predicting protein subcellular localization …
Parameter-efficient fine-tuning on large protein language models improves signal peptide prediction
Signal peptides (SPs) play a crucial role in protein translocation in cells. The development of
large protein language models (PLMs) and prompt-based learning provide a new …
large protein language models (PLMs) and prompt-based learning provide a new …
An allosteric redox switch involved in oxygen protection in a CO2 reductase
Metal-dependent formate dehydrogenases reduce CO2 with high efficiency and selectivity,
but are usually very oxygen sensitive. An exception is Desulfovibrio vulgaris W/Sec-FdhAB …
but are usually very oxygen sensitive. An exception is Desulfovibrio vulgaris W/Sec-FdhAB …
[HTML][HTML] Deep learning frameworks for protein–protein interaction prediction
X Hu, C Feng, T Ling, M Chen - Computational and structural …, 2022 - Elsevier
Protein-protein interactions (PPIs) play key roles in a broad range of biological processes.
The disorder of PPIs often causes various physical and mental diseases, which makes PPIs …
The disorder of PPIs often causes various physical and mental diseases, which makes PPIs …
iRO-3wPseKNC: identify DNA replication origins by three-window-based PseKNC
B Liu, F Weng, DS Huang, KC Chou - Bioinformatics, 2018 - academic.oup.com
Motivation DNA replication is the key of the genetic information transmission, and it is
initiated from the replication origins. Identifying the replication origins is crucial for …
initiated from the replication origins. Identifying the replication origins is crucial for …
DeepTrio: a ternary prediction system for protein–protein interaction using mask multiple parallel convolutional neural networks
Motivation Protein–protein interaction (PPI), as a relative property, is determined by two
binding proteins, which brings a great challenge to design an expert model with an …
binding proteins, which brings a great challenge to design an expert model with an …