A brief survey of machine learning methods in protein sub-Golgi localization
Background: The location of proteins in a cell can provide important clues to their functions
in various biological processes. Thus, the application of machine learning method in the …
in various biological processes. Thus, the application of machine learning method in the …
Deep learning for genomics: A concise overview
Advancements in genomic research such as high-throughput sequencing techniques have
driven modern genomic studies into" big data" disciplines. This data explosion is constantly …
driven modern genomic studies into" big data" disciplines. This data explosion is constantly …
DockQ: a quality measure for protein-protein docking models
The state-of-the-art to assess the structural quality of docking models is currently based on
three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and …
three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and …
Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13
Predicting residue‐residue distance relationships (eg, contacts) has become the key
direction to advance protein structure prediction since 2014 CASP11 experiment, while …
direction to advance protein structure prediction since 2014 CASP11 experiment, while …
DeepQA: improving the estimation of single protein model quality with deep belief networks
Background Protein quality assessment (QA) useful for ranking and selecting protein models
has long been viewed as one of the major challenges for protein tertiary structure prediction …
has long been viewed as one of the major challenges for protein tertiary structure prediction …
PIP-EL: a new ensemble learning method for improved proinflammatory peptide predictions
Proinflammatory cytokines have the capacity to increase inflammatory reaction and play a
central role in first line of defence against invading pathogens. Proinflammatory inducing …
central role in first line of defence against invading pathogens. Proinflammatory inducing …
Survey of AI in cybersecurity for information technology management
L Chan, I Morgan, H Simon… - … IEEE technology & …, 2019 - ieeexplore.ieee.org
Cybersecurity has become an emerging challenge for business information management in
recent years. Artificial Intelligence (AI) is widely used in different field, but it is still relatively …
recent years. Artificial Intelligence (AI) is widely used in different field, but it is still relatively …
Deep learning for genomics: From early neural nets to modern large language models
The data explosion driven by advancements in genomic research, such as high-throughput
sequencing techniques, is constantly challenging conventional methods used in genomics …
sequencing techniques, is constantly challenging conventional methods used in genomics …
QAcon: single model quality assessment using protein structural and contact information with machine learning techniques
Motivation Protein model quality assessment (QA) plays a very important role in protein
structure prediction. It can be divided into two groups of methods: single model and …
structure prediction. It can be divided into two groups of methods: single model and …
[HTML][HTML] Computational prediction of MoRFs, short disorder-to-order transitioning protein binding regions
Molecular recognition features (MoRFs) are short protein-binding regions that undergo
disorder-to-order transitions (induced folding) upon binding protein partners. These regions …
disorder-to-order transitions (induced folding) upon binding protein partners. These regions …