Peptidomics

化学 蛋白质组学 计算生物学 生物化学 鉴定(生物学) 生物 基因 植物
作者
Geert Baggerman,Peter Verleyen,Elke Clynen,Jurgen Huybrechts,Arnold DeLoof,Liliane Schoofs
出处
期刊:Journal of Chromatography B [Elsevier BV]
卷期号:803 (1): 3-16 被引量:127
标识
DOI:10.1016/j.jchromb.2003.07.019
摘要

Peptides occur in the whole animal kingdom, from the least evolved phyla with a very simple nervous system (coelenterates) to the highest vertebrates and are involved in most, if not all, physiological processes in animals. Knowing the amino acid sequence of peptide hormones or neurotransmitters is important since this allows for synthesis of large quantities of peptides to perform further functional analysis. Immunocytochemistry, radioimmunoassays (RIA), enzyme-linked immunosorbant assays (ELISA) and mass spectrometry can then provide information on the temporal and spatial distribution and quantification of the (neuro)peptide. Ever since the 1970s, a wealth of peptides has been discovered and investigated and this flow seems to be far from over. This is partially due to the use of new approaches mainly based on chromatographical purifications as well as molecular biological techniques. Surprisingly, peptides have so far been neglected in most proteomic studies. The finalization of the genome projects has opened new opportunities for rapid identification and functional analysis of (neuro)peptides as well. In analogy with the proteomics technology, where all proteins expressed in a cell or tissue are analyzed, the peptidomic approach aims at the simultaneous visualization and identification of the whole peptidome of a cell or tissue, i.e. all expressed peptides with their post-translational modifications (PTMs). This technology provides us with a fast and efficient tool to analyze the peptides from any tissue. This paper reviews the approaches that have been used so far to achieve this.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
better完成签到 ,获得积分10
刚刚
丘比特应助yx采纳,获得10
1秒前
科研通AI6.4应助铸一字错采纳,获得10
1秒前
1秒前
纳纳椰发布了新的文献求助10
4秒前
peng完成签到 ,获得积分10
4秒前
傲娇的棉花糖完成签到 ,获得积分10
4秒前
6秒前
精明黑猫发布了新的文献求助10
6秒前
可期99关注了科研通微信公众号
6秒前
7秒前
胡紫润发布了新的文献求助10
7秒前
7秒前
北辰南锦完成签到 ,获得积分10
8秒前
+1完成签到,获得积分10
8秒前
YIYI应助loser采纳,获得10
9秒前
9秒前
9秒前
10秒前
11秒前
可恶的鼠发布了新的文献求助10
11秒前
11秒前
科研通AI6.4应助凡阅采纳,获得10
11秒前
李爱国应助nxl采纳,获得10
13秒前
热心小蕊发布了新的文献求助10
14秒前
peng发布了新的文献求助10
15秒前
铸一字错发布了新的文献求助10
15秒前
上官若男应助Kenny采纳,获得10
16秒前
温暖砖头发布了新的文献求助10
16秒前
大模型应助lcl采纳,获得10
18秒前
18秒前
19秒前
21秒前
齐智阳完成签到,获得积分10
22秒前
科目三应助baiyixuan采纳,获得10
23秒前
星星之火完成签到,获得积分10
23秒前
轻松的大米完成签到,获得积分10
23秒前
Geao应助six采纳,获得10
24秒前
Adzuki0812完成签到,获得积分10
24秒前
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
A Psychological Understanding of Criticism and Mental Health 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7752399
求助须知:如何正确求助?哪些是违规求助? 9299500
关于积分的说明 20252744
捐赠科研通 7334666
什么是DOI,文献DOI怎么找? 3310265
关于科研通互助平台的介绍 2461604
邀请新用户注册赠送积分活动 2323001