Computational Approaches to Transcriptome Signatures in the Human Brain
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Owner/Developer: Agilent Technologies
| Country: |
United States of America |
|---|---|
| Languages: |
English |
| Url: |
https://agilenteseminar.webex.com/ec3200/eventcenter/recording/recordAction.do?theAction=poprecord&siteurl=agilenteseminar&entappname=url3200&internalRecordTicket=4832534b00000004d47dea5012b41e8c69e1aea7a6b6b7fd921cde3f1f71af537768640b647b4127&renewticket=0&isurlact=true&format=short&rnd=2506269042&RCID=81488cb164514fb4ba8711fb258eef2e&rID=12540587&needFilter=false&recordID=12540587&apiname=lsr.php&AT=pb&actappname=ec3200&&SP=EC&entactname=%2FnbrRecordingURL.do&actname=%2Feventcenter%2Fframe%2Fg |
| Created: |
18 February 2016 |
| Locations: |
United States of America |
| Description: | The Allen Institute for Brain Science has used large scale Agilent microarray profiling and computational approaches to understanding canonical signatures of gene transcription in the adult human brain. The data set produced by the authors is the largest of its kind, using custom Agilent microarrays with >62,000 probes to measure gene expression levels in >3,700 meticulously macrodissected or lasermicrodissected samples from six adult human brains |
| Format: |
Webinars |
| Presence: |
Optional / Voluntary |
| Access: |
Free |
| Content type: |
Theoretical |
| Duration: |
55 min |
| Target audience: |
Students, Researchers, Regulators and policy-makers, Teachers and educators, Technicians, Managers, Scientific officers / Project managers, Professionals (e.g. veterinarians), General public |
| Target sectors: |
Academia, Industry, Governmental bodies, Contract Research Organizations (CROs), Consulting, SMEs |
| Educational level: |
Continuing Professional Development |
| 3rs relevance: |
Replacement |
| Topics covered: |
Computational methods |
| 3rs coverage: |
Full coverage (a dedicated course) |
| Details on the topic or technology covered: |
This extent of neuroanatomical coverage is unprecedented and provides the neuroscientific community with a resource that has many further possibilities for data mining and analysis. To make sense of this data, we introduce the concept of differential stability (DS), a correlation-based metric that quantifies the extent to which a gene shows reproducible expression patterns across neuroanatomical structures in different individuals . These high-DS genes have a number of interesting properties, including significant enrichment with neuronal functions, disease associations and drug targets. In this presentation we survey the Allen Human Brain Atlas platform, its capabilities and results. |
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