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1,773 results for “Supplementary data,”
Supplementary mass spectonomy data to analyse generation of spliced mutant Kras/RAC2 epitopes
<p><span><span><span><span><span><span><span><span><span><span><span><b><i>In vitro </i></b><b>proteasome processing of neo-splicetopes does not predict their presentation <i>in vivo</i></b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Proteasome catalyzed peptide splicing (PCPS) of cancer-driving antigens could generate attractive neoepitopes to be targeted by TCR-based adoptive T cell therapy. Based on a spliced peptide prediction algorithm TCRs were generated against putative KRAS<sup>G12V</sup> and RAC2<sup>P29L</sup> derived neo-splicetopes with high HLA-A*02:01 binding affinity. TCRs generated in mice with a diverse human TCR repertoire specifically recognized the respective target peptides with high efficacy. However, we failed to detect any neo-splicetope specific T cell response when testing the <i>in vivo</i> neo-splicetope generation and obtained no experimental evidence that the putative KRAS<sup>G12V</sup>- and RAC2<sup>P29L</sup>-derived neo-splicetopes were naturally processed and presented. Furthermore, only the putative RAC2<sup>P29L</sup>-derived neo-splicetopes was generated by <i>in vitro</i> PCPS. Our experiments pose severe questions on the notion that available algorithms or the <i>in vitro </i>PCPS reaction reliably simulate <i>in vivo</i> splicing and argue against the general applicability of an algorithm-driven "reverse immunology" pipeline for the identification of cancer-specific neo-splicetopes.</span></span></span></span></span></span></span></span></span></span></span></p>
Supplementary material 3 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Annual average costs of biological invasions in Singapore. Note the y-axis is on a log10 scale
Supplementary material 2 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Database subset
Supplementary material 3 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S3
Supplementary material 9 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S9
Supplementary material 1 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S1
Supplementary material 7 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S7
Supplementary material 21 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Table S2
Supplementary material 8 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S8
Supplementary material 19 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Figure S4
Supplementary material 18 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Figure S3
Supplementary material 17 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Figure S2
Supplementary material 16 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Figure S1
Supplementary material 11 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S11
Supplementary material 15 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S15
Supplementary material 4 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S4
Supplementary material 2 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S2
Supplementary material 10 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S10
Supplementary material 6 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S6
Supplementary material 20 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
Table S1
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.