Literature DB >> 15465281

High throughput approaches in neuroscience.

C M Morris1, K E Wilson.   

Abstract

Traditional approaches to understanding biological problems are now being advanced with the use of high throughput technologies, which analyse multiple samples simultaneously, or thousands of analytes in a single sample. The application of these technologies in neurochemistry and neuroscience is beginning to be explored and is assisting in the development of new models of drug action, neuroanatomical investigations, and in identifying molecular pathways involved in neurological and psychiatric disease. Tools such as microarray-based gene expression profiling and 2D and multidimensional proteomic methods are uncovering functional components to a wide variety of neuroscience paradigms and the application of these technologies is set to become standard in analysis.

Entities:  

Mesh:

Year:  2004        PMID: 15465281     DOI: 10.1016/j.ijdevneu.2004.07.010

Source DB:  PubMed          Journal:  Int J Dev Neurosci        ISSN: 0736-5748            Impact factor:   2.457


  5 in total

Review 1.  Approaches for targeted proteomics and its potential applications in neuroscience.

Authors:  Sumit Sethi; Dipti Chourasia; Ishwar S Parhar
Journal:  J Biosci       Date:  2015-09       Impact factor: 1.826

2.  Using web ontology language to integrate heterogeneous databases in the neurosciences.

Authors:  Hugo Y K Lam; Luis Marenco; Gordon M Shepherd; Perry L Miller; Kei-Hoi Cheung
Journal:  AMIA Annu Symp Proc       Date:  2006

3.  Odor-evoked gene regulation and visualization in olfactory receptor neurons.

Authors:  Mosi K Bennett; Heather M Kulaga; Randall R Reed
Journal:  Mol Cell Neurosci       Date:  2010-01-18       Impact factor: 4.314

Review 4.  Synaptic proteins as multi-sensor devices of neurotransmission.

Authors:  Guy Brachya; Chava Yanay; Michal Linial
Journal:  BMC Neurosci       Date:  2006-10-30       Impact factor: 3.288

5.  The secrets of a functional synapse--from a computational and experimental viewpoint.

Authors:  Michal Linial
Journal:  BMC Bioinformatics       Date:  2006-03-20       Impact factor: 3.169

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.