Results 111 to 120 of about 1,386,749 (339)

Deep learning methods for protein structure prediction

MedComm – Future Medicine
Protein structure prediction (PSP) has been a prominent topic in bioinformatics and computational biology, aiming to predict protein function and structure from sequence data.
Yiming Qin, Zihan Chen, Ye Peng, Ying Xiao, Tian Zhong, Xi Yu   +5 more
doaj   +1 more source

Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.

PLoS Computational Biology
As of now, more than 60 years have passed since the first determination of protein structures through crystallography, and a significant portion of protein structures can be predicted by computers. This is due to the groundbreaking enhancement in protein
Hyeonuk Woo, Yubeen Kim, Chaok Seok
doaj   +1 more source

Protein structure prediction in genomics [PDF]

Briefings in Bioinformatics, 2001
As the number of completely sequenced genomes rapidly increases, including now the complete Human Genome sequence, the post-genomic problems of genome-scale protein structure determination and the issue of gene function identification become ever more pressing.
openaire   +2 more sources

Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction [PDF]

, 2014
Jian Zhou, Olga G. Troyanskaya
openalex   +1 more source

Review for "High‐accuracy protein structure prediction in CASP14"

, 2021

openalex   +1 more source

Secondary Protein Structure Prediction Using Neural Networks [PDF]

, 2022
Sidharth Malhotra, Robin Walters
openalex   +1 more source

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

Proteins: Structure, Function, and Bioinformatics, 2019
We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13. Submissions were made by three free‐modeling (FM) methods which combine the predictions of three neural networks. All three systems were guided by
A. Senior, Richard Evans, J. Jumper, J. Kirkpatrick, L. Sifre, Tim Green, Chongli Qin, Augustin Žídek, A. W. R. Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, K. Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, K. Kavukcuoglu, D. Hassabis   +18 more
semanticscholar   +1 more source

Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA

Molecular Oncology, EarlyView.
Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson, Anders Lade Nielsen, Boe Sandahl Sorensen   +2 more
wiley   +1 more source

Limitations of Protein Structure Prediction Algorithms in Therapeutic Protein Development

BioMedInformatics
The three-dimensional protein structure is pivotal in comprehending biological phenomena. It directly governs protein function and hence aids in drug discovery. The development of protein prediction algorithms, such as AlphaFold2, ESMFold, and trRosetta,
Sarfaraz K. Niazi, Zamara Mariam, Rehan Z. Paracha   +2 more
doaj   +1 more source

In silico Sequence Analysis, Homology Modeling and Function Annotation of Ocimum basilicum Hypothetical Protein G1CT28_OCIBA [PDF]

International Journal Bioautomation, 2012
Ocimum basilicum is commonly known as sweet basil and belongs to the Lamiaceae Family. Ocimum basilicum has great therapeutic benefits and can be used for lowering blood pressure, as an antispasmodic as well as cleansing the blood.
Sobia Idrees, Shahid Nadeem, Samia Kanwal, Beenish Ehsan, Ayesha Yousaf, Sameera Nadeem, Muhammad Ibrahim Rajoka   +6 more
doaj