Results 121 to 130 of about 410,461 (311)

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

open access: yesMolecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski   +12 more
wiley   +1 more source

FDserver: A web service for protein folding research

open access: yes, 2008
*Summary:* To facilitate the study of protein folding, we have developed a web service for protein folding rate and folding type prediction as well as for the calculation of a variety of topological parameters of protein structure, which is freely ...
Ling-Ling Chen   +2 more
core  

An assessment of feature relevance in predicting protein function from sequence [PDF]

open access: yes, 2004
Improving the performance of protein function prediction is the ultimate goal for a bioinformatician working in functional genomics. The classical prediction approach is to employ pairwise sequence alignments. However this method often faces difficulties
Tan, AC   +17 more
core   +1 more source

Deep learning methods for protein structure prediction

open access: yesMedComm – 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   +5 more
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

open access: yesMolecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim   +3 more
wiley   +1 more source

Opportunities and challenges in protein structure prediction

open access: yesQuantitative Biology
Deep learning methods, particularly exemplified by AlphaFold2, have revolutionized the field of protein structure prediction—an achievement recognized by the 2024 Nobel Prize in Chemistry awarded to its core developers.
Wenkai Wang   +3 more
doaj   +1 more source

Structure-based prediction of protein-protein interaction network in rice

open access: yesGenetics and Molecular Biology
Comprehensive protein-protein interaction (PPI) maps are critical for understanding the functional organization of the proteome, but challenging to produce experimentally.
Fangnan Sun   +6 more
doaj   +1 more source

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

open access: yesInternational 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   +6 more
doaj  

ZW4864‐mediated inhibition of the β‐catenin/BCL9/BCL9L complex reveals therapeutic potential in bladder cancer

open access: yesMolecular Oncology, EarlyView.
BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi   +11 more
wiley   +1 more source

PROTEUS2: A Web Server for Comprehensive Protein Structure Prediction and Structure-Based Annotation

open access: yes, 2008
PROTEUS2 is a web server designed to support comprehensive protein structure prediction and structure-based annotation. PROTEUS2 accepts either single sequences (for directed studies) or multiple sequences (for whole proteome annotation) and predicts the
Wishart, D.S.   +5 more
core   +1 more source

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