Results 171 to 180 of about 760,069 (270)

Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning. [PDF]

Nat Biotechnol, 2023
Stahl K, Graziadei A, Dau T, Brock O, Rappsilber J.   +4 more
europepmc   +1 more source

Building a Framework for Sexual and Reproductive Health Care in the Rheumatology Context: Content and Approaches

Arthritis Care &Research, EarlyView.
People with systemic autoimmune and rheumatic diseases (SARDs) are at higher risk than the general population of experiencing adverse pregnancy and perinatal outcomes such as preeclampsia, intrauterine growth restriction, and maternal and/or fetal death.
Mehret Birru Talabi, Sonya Borrero
wiley   +1 more source

Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER. [PDF]

Nat Biotechnol
Zheng W, Wuyun Q, Li Y, Liu Q, Zhou X, Peng C, Zhu Y, Freddolino L, Zhang Y.   +8 more
europepmc   +1 more source

Associations of Rheumatoid Arthritis Disease Activity With Frailty Over Five Years of Follow‐up

Arthritis Care &Research, EarlyView.
Objective To evaluate whether rheumatoid arthritis (RA) disease activity is associated with frailty both in cross‐section and longitudinally. Methods Participants within the Veterans Affairs Rheumatoid Arthritis (VARA) registry enrolled from 2003 to 2022 were included.
Courtney N. Loecker, Yangyuna Yang, Punyasha Roul, Aaron Baraff, Myra S. Schmaderer, Lani Zimmerman, Kaleb Michaud, Namrata Singh, Grant W. Cannon, Gary Kunkel, Ted R. Mikuls, Ariela R. Orkaby, Joshua F. Baker, Bryant R. England, Katherine D. Wysham   +14 more
wiley   +1 more source

Advancements in one-dimensional protein structure prediction using machine learning and deep learning. [PDF]

Comput Struct Biotechnol J
Alanazi W, Meng D, Pollastri G.
europepmc   +1 more source

DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function. [PDF]

Bioinformatics, 2023
Lee JW, Won JH, Jeon S, Choo Y, Yeon Y, Oh JS, Kim M, Kim S, Joung I, Jang C, Lee SJ, Kim TH, Jin KH, Song G, Kim ES, Yoo J, Paek E, Noh YK, Joo K.   +18 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

LightRoseTTA: High-Efficient and Accurate Protein Structure Prediction Using a Light-Weight Deep Graph Model. [PDF]

Adv Sci (Weinh)
Wang X, Zhang T, Liu G, Cui Z, Zeng Z, Long C, Zheng W, Yang J.   +7 more
europepmc   +1 more source

Biodegradable and Recyclable Luminescent Mixed‐Matrix‐Membranes, Hydrogels, and Cryogels based on Nanoscale Metal‐Organic Frameworks and Biopolymers

Advanced Functional Materials, EarlyView.
The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner, Julian Burkhart, Kateryna Borysova, Chiara Mazzariol, Klaus Müller‐Buschbaum   +4 more
wiley   +1 more source

Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction. [PDF]

Curr Opin Struct Biol
Chakravarty D, Lee M, Porter LL.
europepmc   +1 more source