例如:"lncRNA", "apoptosis", "WRKY"

A visual intracellular classification strategy for uncharacterized human proteins.

Exp. Cell Res.2000 Aug 25;259(1):239-46
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
+ et al

[No authors listed]

Author information
  • {{index+1}} {{ organisation }}

摘要


The human cDNA and genomic sequencing projects will result in the identification and isolation of some 140,000 genes, the majority of which lack predicted functions and for which the cellular localizations are not known. The identification and characterization of protein components of specific cell structures and machineries are essential steps not only toward defining functions of genes but also toward understanding cell function and regulation. We describe here a new approach, termed PROLOC, which uses full-length cDNAs for systematic classification of novel proteins as a functional pointer. We have PCR-amplified 25 uncharacterized human genes and expressed the encoded proteins as GFP fusions in a human cell line. This pilot project has identified novel proteins associated with the nucleolus, mitochondria, the ER, the ER-Golgi-intermediate compartment (ERGIC), the GC, the plasma membrane, and cytoplasmic foci. This visual classification approach may be scaled up to handle a large number of novel genes and permit the generation of a global cellular protein localization map. Such information should be valuable for many aspects of functional genomics and cell biology.

KEYWORDS: {{ getKeywords(articleDetailText.words) }}

基因功能


  • {{$index+1}}.{{ gene }}

图表


原始数据


 保存测序数据
Sample name
Organism Experiment title Sample type Library instrument Attributes
{{attr}}
{{ dataList.sampleTitle }}
{{ dataList.organism }} {{ dataList.expermentTitle }} {{ dataList.sampleType }} {{ dataList.libraryInstrument }} {{ showAttributeName(index,attr,dataList.attributes) }}

文献解读