E-PROT-83
Ontology highlight
ABSTRACT:
PROVIDER: E-PROT-83 | ExpressionAtlas | 2022-01-14
REPOSITORIES: ExpressionAtlas
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Project description:Proteome changes during mouse brain ageing
2022-01-14 | E-PROT-75 | ExpressionAtlas
Project description:Transcriptome and proteome analysis of early embryonic mouse brain development
| PRJNA100939 | ENA
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:To investigate the connection between changes of mRNA and protein expression in the brain during aging, we compared the transcriptome and proteome of the mouse cortex. We profiled gene expression in the mouse cortex using data obtained from RNA-seq of three individuals at 6-months old and three individuals at 24-months old.
2023-03-01 | GSE218637 | GEO
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:We have correlated transciptomics, proteomics and toponomics analyses of hippocampus tissue of inbred C57/BL6 mice to analyse the interrelationship of expressed genes and proteins at different levels of organization. We find that transcriptome and proteome levels of function are highly conserved between different mice, while the topological organization (the toponome) of protein clusters in synapses of the hippocampus is highly individual, with only few interindividual overlaps (0.15 %). In striking contrast, the overall spatial patterns of individual synaptic states, defined by protein clusters, have boundaries within a strict and non-individual spatial frame of the total synaptic network. The findings are the first to provide insight in the systems biology of gene expression on transcriptome, proteome and toponome levels of function in the same brain subregion. The approach may lay the ground for designing studies of neurodegeneration in mouse models and human brains. Keywords: brain proteome, transcriptome, toponome, synapses
2008-05-29 | GSE8239 | 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:MicroRNA microarrays and RNA expression arrays were used to identify functional signaling between neural stem cell progenitor cells (NSPC) and brain endothelial cells (EC) that are critical during embryonic development and tissue repair following brain injury. Mouse neural stem /progenitor cells (NSPC) and brain endothelial cells (EC) were co-cultured to identify changes in gene and miRNA profiles induced in ECs under the influence of NSPCs
2011-08-31 | E-GEOD-29759 | biostudies-arrayexpress
Project description:Proteomics of Brain Proteome Revealed Altered Mitochondrial Function in Alzheimer Disease
2022-01-07 | E-PROT-39 | ExpressionAtlas