E-PROT-109
Ontology highlight
ABSTRACT:
PROVIDER: E-PROT-109 | ExpressionAtlas | 2023-06-21
REPOSITORIES: ExpressionAtlas
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Project description:Proteomics of thyroid tumours - Proteomics of thyroid tumours provides new insights into their molecular composition and changes associated with malignancy
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Project description:Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.
| S-EPMC3393831 | biostudies-literature
Project description:Identification and validation of stage-associated serum biomarkers in colorectal cancer stages.
2023-06-21 | E-PROT-107 | ExpressionAtlas
Project description:Proteomics of the dentate gyrus reveals semantic dementia specific molecular pathology
2024-06-05 | E-PROT-148 | ExpressionAtlas
Project description:Sex differences in the molecular signature of the developing mouse hippocampus
2022-01-14 | E-PROT-84 | ExpressionAtlas
Project description:BackgroundThe accuracy of protein 3D structure prediction has been dramatically improved with the help of advances in deep learning. In the recent CASP14, Deepmind demonstrated that their new version of AlphaFold (AF) produces highly accurate 3D models almost close to experimental structures. The success of AF shows that the multiple sequence alignment of a sequence contains rich evolutionary information, leading to accurate 3D models. Despite the success of AF, only the prediction code is open, and training a similar model requires a vast amount of computational resources. Thus, developing a lighter prediction model is still necessary.ResultsIn this study, we propose a new protein 3D structure modeling method, A-Prot, using MSA Transformer, one of the state-of-the-art protein language models. An MSA feature tensor and row attention maps are extracted and converted into 2D residue-residue distance and dihedral angle predictions for a given MSA. We demonstrated that A-Prot predicts long-range contacts better than the existing methods. Additionally, we modeled the 3D structures of the free modeling and hard template-based modeling targets of CASP14. The assessment shows that the A-Prot models are more accurate than most top server groups of CASP14.ConclusionThese results imply that A-Prot accurately captures the evolutionary and structural information of proteins with relatively low computational cost. Thus, A-Prot can provide a clue for the development of other protein property prediction methods.
| S-EPMC8925138 | biostudies-literature
Project description:Molecular characterization of colorectal adenomas reveals POFUT1 as a candidate driver of tumor progression
2024-06-05 | E-PROT-138 | ExpressionAtlas
Project description:The transcatheter aortic valve replacement (TAVR) procedure has emerged as a minimally invasive treatment for patients with aortic valve stenosis (AVS). However, alterations in serum factor composition and biological activity after TAVR remain unknown. Here, we quantified the systemic inflammatory effects of the TAVR procedure and hypothesized that alterations in serum factor composition would modulate valve and cardiac fibrosis. Serum samples were obtained from patients with AVS immediately before their TAVR procedure (pre-TAVR) and about one month afterwards (post-TAVR). Aptamer-based proteomic profiling revealed alterations in post-TAVR serum composition, and ontological analysis identified inflammatory macrophage factors implicated in myofibroblast activation and deactivation. Hydrogel biomaterials used as valve matrix mimics demonstrated that post-TAVR serum reduced myofibroblast activation of valvular interstitial cells relative to pre-TAVR serum from the same patient. Transcriptomics and curated network analysis revealed a shift in myofibroblast phenotype from pre-TAVR to post-TAVR and identified p38 MAPK signaling as one pathway involved in pre-TAVR-mediated myofibroblast activation. Post-TAVR serum deactivated valve and cardiac myofibroblasts initially exposed to pre-TAVR serum to a quiescent fibroblast phenotype. Our in vitro deactivation data correlated with patient echocardiography data and multi-morbidity scores, and correlations were dependent upon hydrogel stiffness. Sex differences in cellular responses to male and female sera were also observed and may corroborate clinical observations regarding sex-specific TAVR outcomes. Together, our observations support the hypothesis that alterations in serum composition after a TAVR procedure may promote an anti-fibrotic fibroblast phenotype.
2019-09-11 | GSE133529 | GEO
Project description:The ever-growing global health threat of antibiotic resistance is compelling researchers to explore alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are emerging as a promising solution to fill this need. Naturally occurring AMPs are produced by all forms of life as part of the innate immune system. High-throughput bioinformatics tools have enabled fast and large-scale discovery of AMPs from genomic, transcriptomic, and proteomic resources of selected organisms. Public protein sequence databases, comprising over 200 million records and growing, serve as comprehensive compendia of sequences from a broad range of source organisms. Yet, large-scale in silico probing of those databases for novel AMP discovery using modern deep learning techniques has rarely been reported. In the present study, we propose an AMP mining workflow to predict novel AMPs from the UniProtKB/Swiss-Prot database using the AMP prediction tool, AMPlify, as its discovery engine. Using this workflow, we identified 8008 novel putative AMPs from all eukaryotic sequences in the database. Focusing on the practical use of AMPs as suitable antimicrobial agents with applications in the poultry industry, we prioritized 40 of those AMPs based on their similarities to known chicken AMPs in predicted structures. In our tests, 13 out of the 38 successfully synthesized peptides showed antimicrobial activity against Escherichia coli and/or Staphylococcus aureus. AMPlify and the companion scripts supporting the AMP mining workflow presented herein are publicly available at https://github.com/bcgsc/AMPlify.
| S-EPMC11917140 | biostudies-literature
Project description:Interventions: Healthy control group:no;pixushire:no;shireyunjie:no
Primary outcome(s): Analysis of human serum metabolites;Analysis of composition of intestinal flora
Study Design: Factorial
| 2704946 | ecrin-mdr-crc