Discerning of Antimicrobial Peptides from Whole Genome Sequenced Temperate Fruit Crops

Antimicrobial peptide sequences from 5 temperate fruit crops (apple, blueberry, peach, raspberry and strawberry) were extracted in-silico. Two methods was used to extract the sequences, homology prediction as well as machine learning prediction using software tools. The extracted possible AMP sequences were analyzed for their physico-chemical properties and then categorized according to the same. All the possible AMP sequences are stored in a categorized worksheet. The data can be carried forward for further computational research or can be synthesized for wet lab works.

本数据集针对5种温带果树作物（苹果、蓝莓、桃、树莓及草莓）的抗菌肽（Antimicrobial Peptide，AMP）序列开展计算机模拟（in-silico）提取。序列提取共采用两种方法：同源性预测法，以及依托软件工具实现的机器学习预测法。随后对所提取的潜在抗菌肽序列的理化性质进行分析，并基于该性质完成分类。所有潜在抗菌肽序列均存储于分类工作表中。本数据集可用于后续计算研究，或经合成后用于湿实验室实验。