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Merck
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重要文件

WH0054206M1

Sigma-Aldrich

抗-ERRFI1单克隆抗体 小鼠抗

clone 2B9, purified immunoglobulin, buffered aqueous solution

同義詞:

抗-ERBB受体反馈抑制因子1, 抗-GENE33, 抗-MIG6, 抗-RALT

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About This Item

MDL號碼:
分類程式碼代碼:
12352203
NACRES:
NA.41

生物源

mouse

品質等級

共軛

unconjugated

抗體表格

purified immunoglobulin

抗體產品種類

primary antibodies

無性繁殖

2B9, monoclonal

形狀

buffered aqueous solution

物種活性

human

技術

indirect ELISA: suitable
western blot: 1-5 μg/mL

同型

IgG1κ

GenBank登錄號

UniProt登錄號

運輸包裝

dry ice

儲存溫度

−20°C

目標翻譯後修改

unmodified

基因資訊

human ... ERRFI1(54206)

一般說明

ERRFI1是一种细胞质蛋白,表达随细胞生长而上调(Wick et al., 1995 [PubMed 7641805])。它与大鼠基因-33的蛋白产物具有显著同源性,经细胞应激诱导产生并介导细胞信号传导(Makkinje et al., 2000 [PubMed 10749885]; Fiorentino et al., 2000 [PubMed 11003669])。[来源:OMIM]

免疫原

ERRFI1 (NP_061821, 111 a.a.~ 220 a.a)带有GST标签的部分重组蛋白。仅GST标签的分子量为26 KDa。

序列
VVCGFKKLTVNGVCASTPPLTPIKNSPSLFPCAPLCERGSRPLPPLPISEALSLDDTDCEVEFLTSSDTDFLLEDSTLSDFKYDVPGRRSFRGCGQINYAYFDTPAVSAA

外觀

溶于pH7.4的磷酸盐缓冲盐水中的溶液

法律資訊

GenBank is a registered trademark of United States Department of Health and Human Services

免責聲明

除非我们的产品目录或产品附带的其他公司文档另有说明,否则我们的产品仅供研究使用,不得用于任何其他目的,包括但不限于未经授权的商业用途、体外诊断用途、离体或体内治疗用途或任何类型的人类或动物食用或应用。

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儲存類別代碼

10 - Combustible liquids

水污染物質分類(WGK)

nwg

閃點(°F)

Not applicable

閃點(°C)

Not applicable

個人防護裝備

Eyeshields, Gloves, multi-purpose combination respirator cartridge (US)


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分析證明 (COA)

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存取文件庫

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Journal of cell communication and signaling (2022-10-26)
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Lixian Liu et al.
Frontiers in cell and developmental biology, 9, 634242-634242 (2021-03-12)
The mitogen-inducible gene 6 (MIG6) is an adaptor protein widely expressed in vascular endothelial cells. However, it remains unknown thus far whether it plays a role in angiogenesis. Here, using comprehensive in vitro and in vivo model systems, we unveil
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Molecular therapy. Methods & clinical development, 23, 241-253 (2021-10-28)
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Steven M Hill et al.
Cell systems, 4(1), 73-83 (2016-12-27)
Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate

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