Results 111 to 120 of about 1,677,396 (366)
Bivariate estimation of distribution algorithms for protein structure prediction. [PDF]
, 2014 A real-valued bivariate ‘Estimation of Distribution Algorithm’ specific for the ab initio and full-atom Protein Structure Prediction problem is proposed. It is known that this is a multidimensional and multimodal problem.
Bonetti, Daniel +6 more
core +1 more source
Single‐cell insights into the role of T cells in B‐cell malignancies
FEBS Letters, EarlyView.Single‐cell technologies have transformed our understanding of T cell–tumor cell interactions in B‐cell malignancies, revealing new T‐cell subsets, functional states, and immune evasion mechanisms. This Review synthesizes these findings, highlighting the roles of T cells in pathogenesis, progression, and therapy response, and underscoring their ...
Laura Llaó‐Cid
wiley +1 more source
Protein structure prediction and analysis using the Robetta server
Nucleic Acids Res., 2004 The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated ...
David E. Kim, D. Chivian, D. Baker
semanticscholar +1 more source
FEBS Letters, EarlyView.In the adult T‐cell leukemia/lymphoma (ATL) cell line ED, the human T‐cell leukemia virus type 1 (HTLV‐1) provirus was integrated into the intron of the ift81 gene in the antisense orientation. Despite this integration, both the intact ift81 and the viral oncogene hbz were simultaneously expressed, likely due to the functional insufficiency of viral ...
Mayuko Yagi +5 more
wiley +1 more source
Recoverable One-dimensional Encoding of Three-dimensional Protein Structures
, 2005 Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence.
A. R. Kinjo +10 more
core +2 more sources
BMC Bioinformatics, 2021 Background Statistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein–protein interaction (PPI) structures.
Joaquim Aguirre-Plans +9 more
doaj +1 more source
Molecular Oncology, EarlyView.MET variants in the N‐lobe of the kinase domain, found in hereditary papillary renal cell carcinoma, require ligand stimulation to promote cell transformation, in contrast to other RTK variants. This suggests that HGF expression in the microenvironment is important for tumor growth in such patients. Their sensitivity to MET inhibitors opens the way for
Célia Guérin +14 more
wiley +1 more source
Knowledge-based energy functions for computational studies of proteins
, 2006 This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design.
A. Ben-Naim +123 more
core +1 more source
Critical assessment of methods of protein structure prediction (CASP)—Round XIII
Proteins: Structure, Function, and Bioinformatics, 2019 CASP (critical assessment of structure prediction) assesses the state of the art in modeling protein structure from amino acid sequence. The most recent experiment (CASP13 held in 2018) saw dramatic progress in structure modeling without use of ...
A. Kryshtafovych +4 more
semanticscholar +1 more source
Improved protein structure prediction by deep learning irrespective of co-evolution information
Nature Machine Intelligence, 2020 Predicting the tertiary structure of a protein from its primary sequence has been greatly improved by integrating deep learning and co-evolutionary analysis, as shown in CASP13 and CASP14. We describe our latest study of this idea, analysing the efficacy
Jinbo Xu, Matthew McPartlon, Jin Li
semanticscholar +1 more source