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.

本数据集通过计算机模拟（in silico）方法，从苹果、蓝莓、桃、树莓、草莓这5种温带果树作物中提取抗菌肽（Antimicrobial peptide，AMP）序列。本次序列提取采用两类方法：同源预测法，以及依托专用软件工具开展的机器学习预测法。针对所提取的候选AMP序列，研究人员对其理化性质进行了分析，并依据上述性质完成分类。所有候选AMP序列均存储于分类后的工作表内。该数据集既可用于后续的计算类研究，也可经合成后用于实体实验室的湿实验工作。