<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Berson E</submitter><funding>NIA NIH HHS</funding><funding>NCRR NIH HHS</funding><funding>Nancy and Buster Alvord Endowment</funding><funding>NHLBI NIH HHS</funding><funding>National Institutes of Health</funding><funding>NIGMS NIH HHS</funding><pagination>13849</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10449792</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>13(1)</volume><pubmed_abstract>Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 </pubmed_abstract><journal>Scientific reports</journal><pubmed_title>Cross-species comparative analysis of single presynapses.</pubmed_title><pmcid>PMC10449792</pmcid><funding_grant_id>HL122393</funding_grant_id><funding_grant_id>U19 AG066567</funding_grant_id><funding_grant_id>AG057915</funding_grant_id><funding_grant_id>R01 HL122393</funding_grant_id><funding_grant_id>AG058829</funding_grant_id><funding_grant_id>UF1 AG057707</funding_grant_id><funding_grant_id>R01 AG057915</funding_grant_id><funding_grant_id>AG049638</funding_grant_id><funding_grant_id>AG068279</funding_grant_id><funding_grant_id>R01 AG056287</funding_grant_id><funding_grant_id>HL087103</funding_grant_id><funding_grant_id>P30 AG066509</funding_grant_id><funding_grant_id>RF1 AG077443</funding_grant_id><funding_grant_id>R01 AG068279</funding_grant_id><funding_grant_id>P30 AG049638</funding_grant_id><funding_grant_id>RF1 AG058829</funding_grant_id><funding_grant_id>GM138353</funding_grant_id><funding_grant_id>R01 HL087103</funding_grant_id><funding_grant_id>P30 AG072947</funding_grant_id><funding_grant_id>S10 RR027431</funding_grant_id><funding_grant_id>R35 GM138353</funding_grant_id><pubmed_authors>Bendall SC</pubmed_authors><pubmed_authors>Postupna N</pubmed_authors><pubmed_authors>Becker M</pubmed_authors><pubmed_authors>Craft S</pubmed_authors><pubmed_authors>Gajera CR</pubmed_authors><pubmed_authors>De Francesco D</pubmed_authors><pubmed_authors>Aghaeepour N</pubmed_authors><pubmed_authors>Chang AL</pubmed_authors><pubmed_authors>Register TC</pubmed_authors><pubmed_authors>Montine KS</pubmed_authors><pubmed_authors>Fox EJ</pubmed_authors><pubmed_authors>Ravindra NG</pubmed_authors><pubmed_authors>Phongpreecha T</pubmed_authors><pubmed_authors>Perna A</pubmed_authors><pubmed_authors>Shively CA</pubmed_authors><pubmed_authors>Latimer CS</pubmed_authors><pubmed_authors>Espinosa C</pubmed_authors><pubmed_authors>Berson E</pubmed_authors><pubmed_authors>Keene CD</pubmed_authors><pubmed_authors>Bukhari SA</pubmed_authors><pubmed_authors>Montine TJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>Cross-species comparative analysis of single presynapses.</name><description>Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 </description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Aug</publication><modification>2025-05-29T21:44:38.65Z</modification><creation>2024-11-08T22:52:41.04Z</creation></dates><accession>S-EPMC10449792</accession><cross_references><pubmed>37620363</pubmed><doi>10.1038/s41598-023-40683-8</doi></cross_references></HashMap>