Case Report | DOI: https://doi.org/10.31579/2692-9406/003
*Corresponding Author: Kuo-Chen Chou, Gordon Life Science Institute, Boston, Massachusetts 02478, United States of America.
Citation: Camille Elliott. (2020) How the artificial intelligence tool iSuc-PseOpt is working for predicting lysine succinylation sites in proteins. Biomedical Research and Clinical Reviews. 1(1); DOI: 10.31579/2692-9406/003
Copyright: ©2020 Camille Elliott, This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Received: 06 March 2020 | Accepted: 11 June 2020 | Published: 18 June 2020
Keywords: Keywords
In 2016 a very powerful AI (artificial intelligence) tool has been established for predicting lysine succinylation sites in proteins, one of the most important post modifications in proteins.
To see how the web-server is working, please do the following.
Step 1. Opening the web-server at http://www.jci-bioinfo.cn/iSuc-PseOpt, you will see the top page of iSuc-PseOpt on your computer screen, as shown in Fig.1. Click on the Read Me button to see a brief introduction about this predictor.
Step 2. Either type or copy/paste your query protein sequences into the inputbox at the center of Fig.1. The input sequences should be in the FASTA format. For the examples of sequences in FASTA format, click the Example button right above the input box.
Step 3. Click on the Submit button to see the predicted result. For example, if you use the Sequences in the Example window as the input, after a few seconds, you will see the corresponding predicted results, which is fully consistent with experiment observations.
Step 4. As shown on the lower panel of Fig.1, you may also choose the batch prediction by entering your e-mail address and your desired batch input file (in FASTA format of course) via the Browse button. To see the sample of batch input file, click on the button Batch-example.
Step 5. Click the Data button to download the benchmark dataset used in this study.
Step 6. Click the Citation button to find the relevant papers that document the detailed development and algorithm for iSuc-PseOpt.
It is anticipated that the Web-Server will be very useful because the vast majority of biological scientists can easily get their desired results without the need to go through the complicated equations in [1] that were presented just for the integrity in developing the predictor.
Also, note that the web-server predictor has been developed by strictly observing the guidelines of “Chou’s 5-steps rule” and hence have the following notable merits (see, e.g., [2] and three comprehensive review papers [3-5]: [1] crystal clear in logic development, [2] completely transparent in operation, [3] easily to repeat the reported results by other investigators, [4] with high potential in stimulating other sequence-analyzing methods, and [5] very convenient to be used by the majority of experimental scientists.
It has not escaped our notice that during the development of iDNA6mA-PseKNC web-server, the approach of general pseudo amino acid components [6] or PseAAC [7] had been utilized and hence its accuracy would be much higher than its counterparts, as concurred by many investigators (see, e.g., [8, 9].
For the marvelous and awesome roles of the “5-steps rule” in driving proteome, genome analyses and drug development, see a series of recent papers [10-31]where the rule and its wide applications have been very impressively presented from various aspects or at different angles.
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