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bioRxiv · 10.1101/654277

An Accurate Bioinformatics Tool For Anti-Cancer Peptide Generation Through Deep Learning Omics

Kaushik, A. C.·Wei, D.-Q.
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Abstract

The Anti-cancer targets play crucial role in signalling processes of cells. We have developed an Anti-Cancer Scanner (ACS) tool for identification of Anti-cancer targets in form of peptides. ACS tool also allows fast fingerprinting of the Anti-cancer targets of significance in the current bioinformatics research. There are tools currently available which predicts the above-mentioned features in single platform. In the present work, we have compared the features predicted by ACS with other on-line available methods and evaluated the performance of the ACS tool. ACS scanned the Anti-cancer target protein sequences provided by the user against the Anti-cancer target data-sets. It has been developed in PERL language and it is scalable having an extensible application in bioinformatics with robust coding architecture. It achieves a prediction accuracy of 95%, which is much higher than the existing tools.

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Kaushik, A. C., Wei, D.-Q.. 2019-05-29. An Accurate Bioinformatics Tool For Anti-Cancer Peptide Generation Through Deep Learning Omics. https://doi.org/10.1101/654277

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