Paper Info
Title
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics
Abstract
This paper is a manifesto aimed at computer scientists interested in developing and applying scientific discovery methods. It argues that: science is experiencing an unprecedented "explosion" in the amount of available data; traditional data analysis methods cannot deal with this increased quantity of data; there is an urgent need to automate the process of refining scientific data into scientific knowledge; inductive logic programming (ILP) is a data analysis framework well suited for this task; and exciting new scientific discoveries can be achieved using ILP scientific discovery methods. We describe an example of using ILP to analyse a large and complex bioinformatic database that has produced unexpected and interesting scientific results in functional genomics. We then point a possible way forward to integrating machine learning with scientific databases to form intelligent databases.
Year
DOI
Venue
2007
10.1007/978-3-540-73920-3_13
Computational Discovery of Scientific Knowledge
Keywords
Field
DocType
interesting scientific result,functional genomics,scientific knowledge,scientific data,traditional data analysis method,available data,automatic acquisition,ilp scientific discovery method,data analysis framework,scientific databases,exciting new scientific discovery,scientific discovery method,data analysis,machine learning,data analysis methods
Inductive logic programming,Data science,Scientific discovery,Data analysis,Sociology of scientific knowledge,Computer science,Functional genomics,Discovery science,Scientific technique,Manifesto
Conference
Citations 
PageRank 
References 
1
0.35
21
Authors
4
Name
Order
Citations
PageRank
Ross D. King11774194.85
Andreas Karwath222821.60
Amanda Clare359247.37
Luc Dehaspe475164.94