AntiAngioPred: A Server for Prediction of Anti-Angiogenic Peptides

Welcome to the official repository for AntiAngioPred, a machine learning-based platform developed for predicting anti-angiogenic peptides involved in inhibiting blood vessel formation associated with tumor growth and cancer progression. Web Server: https://webs.iiitd.edu.in/raghava/antiangiopred/ Mirror Server: http://crdd.osdd.net/raghava/antiangiopred/ Brief Description Angiogenesis is the biological process responsible for the formation of new blood vessels and plays a major role in tumor development and cancer metastasis. Anti-angiogenic peptides can suppress this process and are therefore considered promising therapeutic agents for cancer treatment. AntiAngioPred was developed to computationally identify anti-angiogenic peptides using sequence-based machine learning approaches. The study analyzed experimentally validated anti-angiogenic peptides and identified characteristic residue preferences, motifs, and positional patterns associated with angiogenesis inhibition. Multiple predictive models were developed using amino acid composition, dipeptide composition, and binary profile patterns combined with machine learning classifiers such as Support Vector Machines (SVM), Random Forest, Naïve Bayes, and Neural Networks. The platform provides prediction, peptide screening, and peptide mutation analysis modules through a user-friendly web interface for researchers working in peptide therapeutics and computational oncology. Citation Ramaprasad, A. S. E., Singh, S., Raghava, G. P. S., & Venkatesan, S. (2015). AntiAngioPred: A Server for Prediction of Anti-Angiogenic Peptides. PLOS ONE, 10(9), e0136990. https://doi.org/10.1371/journal.pone.0136990 About the Platform AntiAngioPred is an in silico prediction system developed for identifying anti-angiogenic peptides from peptide sequences using machine learning techniques. The platform performs: Anti-angiogenic peptide prediction Multiple peptide screening Mutational analysis of peptides Peptide analog generation The prediction models were trained on experimentally validated peptides collected from: Published literature Patents Swiss-Prot derived negative datasets欢迎来到AntiAngioPred的官方仓库。AntiAngioPred是一款基于机器学习的平台，专为预测参与抑制与肿瘤生长及癌症进展相关的血管生成的抗血管生成肽（anti-angiogenic peptides）而开发。 官方网页服务器：https://webs.iiitd.edu.in/raghava/antiangiopred/ 镜像服务器：http://crdd.osdd.net/raghava/antiangiopred/ ### 简要说明 血管生成（Angiogenesis）是介导新生血管形成的生物学过程，在肿瘤发生发展与癌症转移过程中发挥关键作用。抗血管生成肽可抑制该进程，因此被视为极具潜力的癌症治疗制剂。 AntiAngioPred旨在通过基于序列的机器学习方法，计算性鉴定抗血管生成肽。本研究分析了经实验验证的抗血管生成肽，鉴定出与血管生成抑制相关的特征性氨基酸残基偏好性、基序（motif）及位置分布模式。 本研究采用氨基酸组成、二肽组成、二元特征谱模式，并结合支持向量机（Support Vector Machines, SVM）、随机森林、朴素贝叶斯（Naïve Bayes）以及神经网络等机器学习分类器，构建了多种预测模型。 该平台通过友好易用的网页界面，为肽治疗学及计算肿瘤学领域的研究人员提供预测、肽筛选及肽突变分析三大功能模块。 ### 引用文献 Ramaprasad, A. S. E., Singh, S., Raghava, G. P. S., & Venkatesan, S. (2015). AntiAngioPred：一款抗血管生成肽预测服务器。PLOS ONE, 10(9), e0136990. https://doi.org/10.1371/journal.pone.0136990 ### 平台简介 AntiAngioPred是一款基于机器学习技术的计算机预测系统，用于从肽序列中鉴定抗血管生成肽。 本平台可实现以下功能： - 抗血管生成肽预测 - 多肽筛选 - 肽突变分析 - 肽类似物生成 本平台的预测模型基于以下途径收集的经实验验证的肽进行训练： - 已发表文献 - 专利文献 - 源自Swiss-Prot的阴性数据集