[HTML][HTML] From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare
The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …
advancement has been initiated and shaped by the applications of data-driven, robust, and …
Accelerating biocatalysis discovery with machine learning: a paradigm shift in enzyme engineering, discovery, and design
B Markus, K Andreas, K Arkadij, L Stefan, O Gustav… - ACS …, 2023 - ACS Publications
Emerging computational tools promise to revolutionize protein engineering for biocatalytic
applications and accelerate the development timelines previously needed to optimize an …
applications and accelerate the development timelines previously needed to optimize an …
Protein–protein contact prediction by geometric triangle-aware protein language models
Abstract Information regarding the residue–residue distance between interacting proteins is
important for modelling the structures of protein complexes, as well as being valuable for …
important for modelling the structures of protein complexes, as well as being valuable for …
Open-source machine learning in computational chemistry
The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
Targeted protein degradation: current and emerging approaches for E3 ligase deconvolution
Targeted protein degradation (TPD), including the use of proteolysis-targeting chimeras
(PROTACs) and molecular glue degraders (MGDs) to degrade proteins, is an emerging …
(PROTACs) and molecular glue degraders (MGDs) to degrade proteins, is an emerging …
Plant-based proteins: advanced extraction technologies, interactions, physicochemical and functional properties, food and related applications, and health benefits
Even though plant proteins are more plentiful and affordable than animal proteins in
comparison, direct usage of plant-based proteins (PBPs) is still limited because PBPs are …
comparison, direct usage of plant-based proteins (PBPs) is still limited because PBPs are …
HNSPPI: a hybrid computational model combing network and sequence information for predicting protein–protein interaction
S **e, X **e, X Zhao, F Liu, Y Wang… - Briefings in …, 2023 - academic.oup.com
Most life activities in organisms are regulated through protein complexes, which are mainly
controlled via Protein–Protein Interactions (PPIs). Discovering new interactions between …
controlled via Protein–Protein Interactions (PPIs). Discovering new interactions between …
Enhancing of transport parameters and antifouling properties of PVDF membranes modified with Fe3O4 nanoparticles in the process of proteins fractionation
Polyvinylidene fluoride (PVDF) possesses a broad range of applications, including
membrane separation used for water and wastewater treatment. However, the natural …
membrane separation used for water and wastewater treatment. However, the natural …
[HTML][HTML] ProtInteract: A deep learning framework for predicting protein–protein interactions
Proteins mainly perform their functions by interacting with other proteins. Protein–protein
interactions underpin various biological activities such as metabolic cycles, signal …
interactions underpin various biological activities such as metabolic cycles, signal …
Cracking the black box of deep sequence-based protein–protein interaction prediction
Identifying protein–protein interactions (PPIs) is crucial for deciphering biological pathways.
Numerous prediction methods have been developed as cheap alternatives to biological …
Numerous prediction methods have been developed as cheap alternatives to biological …