.png){kind=icon}
返回
Inductive logic programming for gene regulation prediction
.png){kind=icon}
OA
AI
DOI：10.1007/s10994-007-5037-3.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a systems biology application of ILP, where the goal is to predict the regulation of a gene under a certain condition from binding site information, the state of regulators, and additional information. In the experiments, the boosted Tilde model is on par with the original model by Middendorf et al. based on alternating decision trees (ADTrees), given the same information. Adding functional categorizations and protein-protein interactions, however, it is possible to improve the performance substantially. We believe that decoding the regulation mechanisms of genes is an exciting new application of learning in logic, requiring data integration from various sources and potentially contributing to a better understanding on a system level.
Keyword:
inductive logic programming
relational learning
gene regulation
gene expression
systems biology
期刊
IF:
2.9
论文数:
2.7K
被引数:
3.4W
机构
引用论文
Impact of pH on Activity of Trimethoprim, Fosfomycin, Amikacin, Colistin and Ertapenem in Human Urine.png)
Pharmacology
PharmacologyIF0
PREAI
分享收藏The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomesNUCLEIC ACIDS RESEARCH
OAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏Module networks: identifying regulatory modules and their condition-specific regulators from gene expression dataNATURE GENETICS
NATURE GENETICSIF31.8
PREAI
分享收藏MIPS: A database for protein sequences, homology data and yeast genome informationNUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏
查看更多内容