NBSPred: A support vector machine-based high throughput pipeline for plant resistance protein NBSLRR prediction.
Kushwaha, Sandeep LU ; Chauhan, Pallavi LU ; Hedlund, Katarina LU
and Ahrén, Dag
LU
(2015)
In Bioinformatics
32(8).
p.1223-1225
- Abstract
- The nucleotide binding site-leucine-rich repeats (NBSLRR) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms have explained the regulation of plant immunity, but still, we have limited understanding about plant defence against different pathogens. Identification of R-proteins and proteins having R-protein-like features across the genome, transcriptome and proteome would be highly useful to develop the global understanding of plant defence mechanisms, but it is laborious and time consuming task. Therefore, we have developed a support vector machine (SVM) based high throughput pipeline called NBSPred to differentiate... (More)
- The nucleotide binding site-leucine-rich repeats (NBSLRR) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms have explained the regulation of plant immunity, but still, we have limited understanding about plant defence against different pathogens. Identification of R-proteins and proteins having R-protein-like features across the genome, transcriptome and proteome would be highly useful to develop the global understanding of plant defence mechanisms, but it is laborious and time consuming task. Therefore, we have developed a support vector machine (SVM) based high throughput pipeline called NBSPred to differentiate NBSLRR and NBSLRR-like protein from Non-NBSLRR proteins from genome, transcriptome and protein sequences. The pipeline was tested and validated with input sequences from 3 dicot and 2 monocot plants including Arabidopsis thaliana, Boechera stricta, Brachypodium distachyon Solanum lycopersicum and Zea mays. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8505184
- author
- Kushwaha, Sandeep
LU
; Chauhan, Pallavi
LU
; Hedlund, Katarina
LU
and Ahrén, Dag
LU
- organization
- publishing date
- 2015-12-09
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Bioinformatics
- volume
- 32
- issue
- 8
- pages
- 1223 - 1225
- publisher
- Oxford University Press
- external identifiers
-
- pmid:26656003
- scopus:84966461401
- pmid:26656003
- wos:000374476800017
- ISSN
- 1367-4803
- DOI
- 10.1093/bioinformatics/btv714
- language
- English
- LU publication?
- yes
- id
- 68a8b4e0-ae6c-45d8-ada7-fbf817fd1dd0 (old id 8505184)
- date added to LUP
- 2016-04-01 10:18:09
- date last changed
- 2022-08-05 05:39:20
@article{68a8b4e0-ae6c-45d8-ada7-fbf817fd1dd0,
abstract = {{The nucleotide binding site-leucine-rich repeats (NBSLRR) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms have explained the regulation of plant immunity, but still, we have limited understanding about plant defence against different pathogens. Identification of R-proteins and proteins having R-protein-like features across the genome, transcriptome and proteome would be highly useful to develop the global understanding of plant defence mechanisms, but it is laborious and time consuming task. Therefore, we have developed a support vector machine (SVM) based high throughput pipeline called NBSPred to differentiate NBSLRR and NBSLRR-like protein from Non-NBSLRR proteins from genome, transcriptome and protein sequences. The pipeline was tested and validated with input sequences from 3 dicot and 2 monocot plants including Arabidopsis thaliana, Boechera stricta, Brachypodium distachyon Solanum lycopersicum and Zea mays.}},
author = {{Kushwaha, Sandeep and Chauhan, Pallavi and Hedlund, Katarina and Ahrén, Dag}},
issn = {{1367-4803}},
language = {{eng}},
month = {{12}},
number = {{8}},
pages = {{1223--1225}},
publisher = {{Oxford University Press}},
series = {{Bioinformatics}},
title = {{NBSPred: A support vector machine-based high throughput pipeline for plant resistance protein NBSLRR prediction.}},
url = {{http://dx.doi.org/10.1093/bioinformatics/btv714}},
doi = {{10.1093/bioinformatics/btv714}},
volume = {{32}},
year = {{2015}},
}