NDLI: G-quadruplex Structure Prediction and integration in the GenData2020 data model

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G-quadruplex Structure Prediction and integration in the GenData2020 data model

Content Provider	ACM Digital Library
Author	Pollastri, Gianluca Cristiano, Francesca Prosperi, Mattia Veltri, Pierangelo Tradigo, Giuseppe Alcaro, Stefano Greco, Sergio
Abstract	DNA is a long polymer encoding information of all living organisms. It usually folds in a double-helix shape and packed in chromosomes. Nonetheless DNA exists in many other conformations, including A-DNA, B-DNA and Z-DNA. B-DNA is the most common form found in cells. Non-B DNAs comprise of tetraplex (G-quadruplex), left-handed Z-DNA, and others. Several recent publications have provided significant evidence that non-B DNA structures may play a role in DNA instability and mutagenesis, leading to both DNA rearrangements and increased mutation rates, which are often related with a number of diseases, among which cancer. Studying the structure conformation and probability to find non-B DNA structures on a DNA or RNA sequence may help in studying diseases and selectively inhibit genes as well as designing new drugs. Nevertheless, even if there are some examples of prediction tools, the topic of designing efficient prediction algorithms and tools for G-quadruplex prediction is still in its infancy. As a contribution in this area, we present a set of novel software tools, both pattern-based and machine learning-based which are able to predict G-quadruplex conformations starting from a DNA/RNA input sequence. We show they outperform the state-of-the-art software tools available in literature by comparing their predictive performances. Results of this work have been used to implement a web-based prediction tool available online. We also report about the integration of such a tool with the GenData2020 cloud-based system.
Starting Page	663
Ending Page	670
Page Count	8
File Format	PDF
ISBN	9781450342254
DOI	10.1145/2975167.2985692
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Rna Computational genomics Dna G-quadruplex Prediction
Content Type	Text
Resource Type	Article

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