Prediction and redesign of protein–protein interactions
Progress in Biophysics and Molecular Biology, ISSN: 0079-6107, Vol: 116, Issue: 2, Page: 194-202
2014
- 27Citations
- 76Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations27
- Citation Indexes27
- 27
- CrossRef18
- Captures76
- Readers76
- 76
Article Description
Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function – those mediated by protein–protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0079610714000406; http://dx.doi.org/10.1016/j.pbiomolbio.2014.05.004; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84924070385&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/24878423; https://linkinghub.elsevier.com/retrieve/pii/S0079610714000406
Elsevier BV
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