Name
Abstract | ||
|---|---|---|
Hypotheses are now being automatically produced on an industrial scale by computers in biology, e.g. the annotation of a genome is essentially a large set of hypotheses generated by sequence similarity programs; and robot scientists enable the full automation of a scientific investigation, including generation and testing of research hypotheses.This paper proposes a logically defined way for recording automatically generated hypotheses in machine amenable way. The proposed formalism allows the description of complete hypotheses sets as specified input and output for scientific investigations. The formalism supports the decomposition of research hypotheses into more specialised hypotheses if that is required by an application. Hypotheses are represented in an operational way - it is possible to design an experiment to test them. The explicit formal description of research hypotheses promotes the explicit formal description of the results and conclusions of an investigation. The paper also proposes a framework for automated hypotheses generation. We demonstrate how the key components of the proposed framework are implemented in the Robot Scientist "Adam".A formal representation of automatically generated research hypotheses can help to improve the way humans produce, record, and validate research hypotheses.http://www.aber.ac.uk/en/cs/research/cb/projects/robotscientist/results/ |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1186/2041-1480-2-S2-S9 | J. Biomedical Semantics |
Keywords | Field | DocType |
biomedical research,bioinformatics | Data science,Inductive logic programming,Textual representation,Data mining,Annotation,Computer science,Automation,Robot | Journal |
Volume | Issue | ISSN |
2 | S-2 | 2041-1480 |
Citations | PageRank | References |
9 | 0.81 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Larisa N. Soldatova | 1 | 180 | 20.75 |
| Andrey Rzhetsky | 2 | 1081 | 94.84 |