iFeatureOmega:an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets

化学信息学 接口(物质) 计算机科学 结构生物信息学 图形用户界面 可视化 Web服务器 编码 源代码 用户界面 范围(计算机科学) 计算生物学 生物 数据科学 数据挖掘 生物信息学 程序设计语言 互联网 蛋白质结构 万维网 基因 生物化学 最大气泡压力法 气泡 并行计算
作者
Zhen Chen,Xuhan Liu,Pei Zhao,Chen Li,Yanan Wang,Fuyi Li,Tatsuya Akutsu,Chris Bain,Robin B. Gasser,Junzhou Li,Zuoren Yang,Xin Gao,Lukasz Kurgan,Jiangning Song
出处
期刊:Nucleic Acids Research [Oxford University Press]
卷期号:50 (W1): W434-W447 被引量:55
标识
DOI:10.1093/nar/gkac351
摘要

Abstract The rapid accumulation of molecular data motivates development of innovative approaches to computationally characterize sequences, structures and functions of biological and chemical molecules in an efficient, accessible and accurate manner. Notwithstanding several computational tools that characterize protein or nucleic acids data, there are no one-stop computational toolkits that comprehensively characterize a wide range of biomolecules. We address this vital need by developing a holistic platform that generates features from sequence and structural data for a diverse collection of molecule types. Our freely available and easy-to-use iFeatureOmega platform generates, analyzes and visualizes 189 representations for biological sequences, structures and ligands. To the best of our knowledge, iFeatureOmega provides the largest scope when directly compared to the current solutions, in terms of the number of feature extraction and analysis approaches and coverage of different molecules. We release three versions of iFeatureOmega including a webserver, command line interface and graphical interface to satisfy needs of experienced bioinformaticians and less computer-savvy biologists and biochemists. With the assistance of iFeatureOmega, users can encode their molecular data into representations that facilitate construction of predictive models and analytical studies. We highlight benefits of iFeatureOmega based on three research applications, demonstrating how it can be used to accelerate and streamline research in bioinformatics, computational biology, and cheminformatics areas. The iFeatureOmega webserver is freely available at http://ifeatureomega.erc.monash.edu and the standalone versions can be downloaded from https://github.com/Superzchen/iFeatureOmega-GUI/ and https://github.com/Superzchen/iFeatureOmega-CLI/.

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
在水一方应助熊二浪采纳,获得10
刚刚
dushicheng发布了新的文献求助10
刚刚
飞飞完成签到,获得积分10
刚刚
小蘑菇应助xiaoxiao采纳,获得10
1秒前
苏格拉要有底完成签到 ,获得积分20
1秒前
所所应助木木采纳,获得10
1秒前
感谢超级沁转发科研通微信,获得积分50
1秒前
Millian完成签到 ,获得积分10
2秒前
liu完成签到 ,获得积分10
3秒前
科研通AI2S应助ChenZhangyang采纳,获得30
3秒前
4秒前
感谢悟空转发科研通微信,获得积分50
4秒前
666发布了新的文献求助10
4秒前
酷酷薯片发布了新的文献求助10
5秒前
大个应助小吃货采纳,获得10
5秒前
小马甲应助米莉采纳,获得10
6秒前
兴奋一斩完成签到,获得积分10
6秒前
感谢优秀如雪转发科研通微信,获得积分50
7秒前
huoyan2006发布了新的文献求助10
8秒前
DZQ发布了新的文献求助10
8秒前
8秒前
丘比特应助苏格拉要有底采纳,获得30
9秒前
10秒前
爱听歌的紫菜完成签到 ,获得积分10
10秒前
兴奋一斩发布了新的文献求助10
10秒前
感谢LL爱读书转发科研通微信,获得积分50
10秒前
11秒前
11秒前
11秒前
11秒前
12秒前
DZQ完成签到,获得积分10
12秒前
13秒前
科研通AI5应助控制狗采纳,获得10
13秒前
唔西迪西发布了新的文献求助10
13秒前
14秒前
14秒前
YUMI驳回了惊嵐应助
14秒前
15秒前
顽石完成签到,获得积分10
16秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3542598
求助须知:如何正确求助?哪些是违规求助? 3119973
关于积分的说明 9341143
捐赠科研通 2818043
什么是DOI,文献DOI怎么找? 1549287
邀请新用户注册赠送积分活动 722093
科研通“疑难数据库(出版商)”最低求助积分说明 712928