Learning to predict protein-protein interactions from protein sequences

@article{Gomez2003LearningTP,
  title={Learning to predict protein-protein interactions from protein sequences},
  author={Shawn M. Gomez and William Stafford Noble and Andrey Rzhetsky},
  journal={Bioinformatics},
  year={2003},
  volume={19 15},
  pages={1875-81}
}
In order to understand the molecular machinery of the cell, we need to know about the multitude of protein-protein interactions that allow the cell to function. High-throughput technologies provide some data about these interactions, but so far that data is fairly noisy. Therefore, computational techniques for predicting protein-protein interactions could be of significant value. One approach to predicting interactions in silico is to produce from first principles a detailed model of a… CONTINUE READING
Highly Cited
This paper has 338 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 113 extracted citations

339 Citations

0204060'06'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 339 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 27 references

Similar Papers

Loading similar papers…