H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.
about
A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced DataThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly.Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.
P2860
H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
2014年學術文章
@zh-hant
name
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@en
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@nl
type
label
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@en
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@nl
prefLabel
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@en
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@nl
P2093
P2860
P1476
H-DROP: an SVM based helical d ...... forest and stepwise selection.
@en
P2093
Ryosuke Suzuki
Ryotaro Tsuji
Yutaka Kuroda
P2860
P2888
P304
P356
10.1007/S10822-014-9763-X
P50
P577
2014-06-26T00:00:00Z