已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network

计算机科学 鉴定(生物学) 深度学习 人工智能 计算生物学 人工神经网络 模式识别(心理学) 生物 植物
作者
Shengming Zhou,Y. Z. Zhou,Tian Liu,Juanjuan Zheng,Cangzhi Jia
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:24 (5)
标识
DOI:10.1093/bib/bbad299
摘要

The formation of biomolecular condensates by liquid-liquid phase separation (LLPS) has become a universal mechanism for spatiotemporal coordination of biological activities in cells and has been widely observed to directly regulate the key cellular processes involved in cancer cell pathology. However, the complexity of protein sequences and the diversity of conformations are inherently disordered, which poses great challenges for LLPS protein calculations and experimental research. Herein, we proposed a novel predictor named PredLLPS_PSSM for LLPS protein identification based only on sequence evolution information. Because finding real and reliable samples is the cornerstone of building predictors, we collected anew and collated the LLPS proteins from the latest versions of three databases. By comparing the performance of the position-specific score matrix (PSSM) and word embedding, PredLLPS_PSSM combined PSSM-based information and two deep learning frameworks. Independent tests using three existing independent test datasets and two newly constructed independent test datasets demonstrated the superiority of PredLLPS_PSSM compared with state-of-the-art methods. Furthermore, we tested PredLLPS_PSSM on nine experimentally identified LLPS proteins from three insects that were not included in any of the databases. In addition, the powerful Shapley Additive exPlanation algorithm and heatmap were applied to find the most critical amino acids relevant to LLPS.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
Yao发布了新的文献求助10
1秒前
冕镜发布了新的文献求助10
1秒前
长系青完成签到,获得积分20
2秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
现代青枫应助科研通管家采纳,获得20
2秒前
隐形曼青应助科研通管家采纳,获得10
2秒前
大模型应助科研通管家采纳,获得10
2秒前
xieting完成签到 ,获得积分10
3秒前
Linn发布了新的文献求助10
3秒前
遇more完成签到 ,获得积分10
4秒前
爱笑若冰完成签到,获得积分10
9秒前
11秒前
11秒前
冕镜完成签到,获得积分10
13秒前
17秒前
18秒前
小花生发布了新的文献求助10
18秒前
20秒前
22秒前
24秒前
亦阳完成签到,获得积分10
24秒前
Linn完成签到 ,获得积分20
27秒前
杜佳月发布了新的文献求助10
27秒前
Fancy发布了新的文献求助10
27秒前
28秒前
28秒前
斯文败类应助六两芫荽采纳,获得10
31秒前
32秒前
奶冻完成签到 ,获得积分10
33秒前
34秒前
kk完成签到 ,获得积分10
34秒前
亦阳发布了新的文献求助10
36秒前
小佛爷完成签到 ,获得积分10
39秒前
41秒前
英俊的铭应助香山叶正红采纳,获得10
43秒前
完美世界应助害羞外套采纳,获得10
43秒前
杜佳月完成签到 ,获得积分10
43秒前
现代雅香发布了新的文献求助10
44秒前
45秒前
高分求助中
Spray / Wall-interaction Modelling by Dimensionless Data Analysis 2000
Mathematics and Finite Element Discretizations of Incompressible Navier—Stokes Flows 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
2-Acetyl-1-pyrroline: an important aroma component of cooked rice 500
A real-time energy management strategy based on fuzzy control and ECMS for PHEVs 400
Handbook on People's China (1957) 400
2024 Medicinal Chemistry Reviews 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3189701
求助须知:如何正确求助?哪些是违规求助? 2839039
关于积分的说明 8022544
捐赠科研通 2501894
什么是DOI,文献DOI怎么找? 1336060
科研通“疑难数据库(出版商)”最低求助积分说明 637770
邀请新用户注册赠送积分活动 605848