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EffectorP-3.0:真菌和卵菌细胞中质外体和细胞质效应子的预测
共345个文件
fasta:91个
arff:85个
model:83个
需积分: 50 1 下载量 65 浏览量
2021-03-10
08:20:51
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EffectorP-3.0:真菌和卵菌细胞中质外和细胞质效应子的预测 什么是EffectorP 3.0? 许多真菌和卵菌纲物种正在破坏植物病原体并分泌效应蛋白以促进植物感染。 真菌和卵菌病原体具有多种感染策略,其效应子不具有序列同源性。 但是,效应子仍然具有统一的特性:它们要么位于细胞外,到植物的质外体,要么位于细胞内,到植物的细胞质。 EffectorP 3.0利用这一生物信号,并分别使用了两个分别在质外体和细胞质效应子上训练的机器学习模型。 对于给定的一组分泌的病原体蛋白质,EffectorP 3.0将预测蛋白质是否为: 质外生效应子 细胞质效应子 双重定位的质外体/细胞质效应子 非执行者 什么是EffectorP 3.0? EffectorP不是用于分泌组预测的工具,也不是用于细菌效应预测的工具。 已经对EffectorP进行了训练,可以在分泌组中找到真菌/卵菌体效应子,因
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EffectorP-3.0:真菌和卵菌细胞中质外体和细胞质效应子的预测 (345个子文件)
trainingdata_iteration71_ratio3.arff 274KB
trainingdata_iteration91_ratio3.arff 274KB
trainingdata_iteration1_ratio3.arff 274KB
trainingdata_iteration14_ratio3.arff 274KB
trainingdata_iteration71_ratio3.arff 273KB
trainingdata_iteration64_ratio3.arff 273KB
trainingdata_iteration17_ratio3.arff 273KB
trainingdata_iteration44_ratio3.arff 273KB
trainingdata_iteration67_ratio3.arff 273KB
trainingdata_iteration70_ratio3.arff 273KB
trainingdata_iteration34_ratio3.arff 273KB
trainingdata_iteration14_ratio3.arff 273KB
trainingdata_iteration62_ratio3.arff 272KB
trainingdata_iteration70_ratio3.arff 272KB
trainingdata_iteration32_ratio3.arff 272KB
trainingdata_iteration79_ratio3.arff 272KB
trainingdata_iteration36_ratio3.arff 272KB
trainingdata_iteration36_ratio3.arff 272KB
trainingdata_iteration29_ratio3.arff 272KB
trainingdata_iteration77_ratio3.arff 272KB
trainingdata_iteration1_ratio3.arff 271KB
trainingdata_iteration78_ratio3.arff 271KB
trainingdata_iteration39_ratio3.arff 270KB
trainingdata_iteration76_ratio3.arff 270KB
trainingdata_iteration74_ratio3.arff 268KB
trainingdata_iteration25_ratio3.arff 190KB
trainingdata_iteration64_ratio3.arff 189KB
trainingdata_iteration92_ratio3.arff 189KB
trainingdata_iteration85_ratio3.arff 189KB
trainingdata_iteration91_ratio3.arff 188KB
trainingdata_iteration96_ratio3.arff 188KB
trainingdata_iteration21_ratio3.arff 188KB
trainingdata_iteration58_ratio3.arff 188KB
trainingdata_iteration56_ratio3.arff 188KB
trainingdata_iteration85_ratio3.arff 188KB
trainingdata_iteration34_ratio3.arff 188KB
trainingdata_iteration32_ratio3.arff 188KB
trainingdata_iteration97_ratio3.arff 188KB
trainingdata_iteration23_ratio3.arff 188KB
trainingdata_iteration100_ratio3.arff 188KB
trainingdata_iteration22_ratio3.arff 188KB
trainingdata_iteration13_ratio3.arff 188KB
trainingdata_iteration77_ratio3.arff 188KB
trainingdata_iteration84_ratio3.arff 188KB
trainingdata_iteration41_ratio3.arff 188KB
trainingdata_iteration16_ratio3.arff 188KB
trainingdata_iteration2_ratio3.arff 187KB
trainingdata_iteration46_ratio3.arff 187KB
trainingdata_iteration88_ratio3.arff 187KB
trainingdata_iteration75_ratio3.arff 187KB
trainingdata_iteration95_ratio3.arff 187KB
trainingdata_iteration61_ratio3.arff 186KB
trainingdata_iteration87_ratio3.arff 186KB
trainingdata_iteration31_ratio3.arff 185KB
trainingdata_iteration85_ratio3.arff 185KB
trainingdata_iteration80_ratio3.arff 159KB
trainingdata_iteration40_ratio3.arff 159KB
trainingdata_iteration77_ratio3.arff 159KB
trainingdata_iteration82_ratio3.arff 158KB
trainingdata_iteration19_ratio3.arff 158KB
trainingdata_iteration78_ratio3.arff 158KB
trainingdata_iteration19_ratio3.arff 158KB
trainingdata_iteration46_ratio3.arff 158KB
trainingdata_iteration9_ratio3.arff 158KB
trainingdata_iteration49_ratio3.arff 157KB
trainingdata_iteration92_ratio3.arff 157KB
trainingdata_iteration29_ratio3.arff 157KB
trainingdata_iteration92_ratio3.arff 157KB
trainingdata_iteration98_ratio3.arff 157KB
trainingdata_iteration46_ratio3.arff 157KB
trainingdata_iteration76_ratio3.arff 157KB
trainingdata_iteration70_ratio3.arff 157KB
trainingdata_iteration61_ratio3.arff 157KB
trainingdata_iteration25_ratio3.arff 157KB
trainingdata_iteration95_ratio3.arff 157KB
trainingdata_iteration47_ratio3.arff 157KB
trainingdata_iteration26_ratio3.arff 157KB
trainingdata_iteration100_ratio3.arff 157KB
trainingdata_iteration78_ratio3.arff 156KB
trainingdata_iteration31_ratio3.arff 156KB
trainingdata_iteration91_ratio3.arff 156KB
trainingdata_iteration32_ratio3.arff 156KB
trainingdata_iteration79_ratio3.arff 156KB
trainingdata_iteration98_ratio3.arff 156KB
trainingdata_iteration53_ratio3.arff 155KB
NEGATIVE_TRAININGSET_iteration71_ratio3.fasta 152KB
NEGATIVE_TRAININGSET_iteration14_ratio3.fasta 148KB
NEGATIVE_TRAININGSET_iteration79_ratio3.fasta 141KB
NEGATIVE_TRAININGSET_iteration91_ratio3.fasta 140KB
NEGATIVE_TRAININGSET_iteration44_ratio3.fasta 139KB
NEGATIVE_TRAININGSET_iteration67_ratio3.fasta 136KB
NEGATIVE_TRAININGSET_iteration62_ratio3.fasta 136KB
NEGATIVE_TRAININGSET_iteration70_ratio3.fasta 136KB
NEGATIVE_TRAININGSET_iteration64_ratio3.fasta 135KB
NEGATIVE_TRAININGSET_iteration32_ratio3.fasta 132KB
NEGATIVE_TRAININGSET_iteration1_ratio3.fasta 132KB
NEGATIVE_TRAININGSET_iteration78_ratio3.fasta 131KB
NEGATIVE_TRAININGSET_iteration36_ratio3.fasta 130KB
NEGATIVE_TRAININGSET_iteration1_ratio3.fasta 129KB
NEGATIVE_TRAININGSET_iteration34_ratio3.fasta 128KB
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