Biotic Stress Protein Tools

This page provides a comprehensive repository of tools dedicated to the prediction and analysis of biotic stress-related proteins. These tools are designed to support researchers in identifying, characterizing, and understanding proteins involved in plant responses to abiotic stress, offering valuable resources for advancing crop resilience and agricultural research.

Name	Year	Description	PubMed ID
PlantDRPpred	2024	Combines alignment-based and alignment-free methods for predicting plant resistance proteins.	39580673
NBSPred	2016	A high-throughput support vector machine pipeline for predicting plant resistance protein NBS-LRRs.	26656003
ResCAP	2021	Predicts plant resistance genes and generates probes for resistance gene sequence capture.	36700100
NLR-parser	2015	Rapidly annotates plant NLR complements.	25586514
DRPPP	2016	Machine-learning-based tool for predicting disease resistance proteins in plants.	27658260
prPred	2020	Predicts plant resistance proteins using k-spaced amino acid (group) pairs.	33553134
StackRPred	2022	Predicts plant resistance proteins using pairwise energy content and stacking framework.	35712582
prPred_DRLF	2022	Predicts plant resistance proteins using deep representation learning features.	34569713

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