research-article

GOLAM: A Framework for Analyzing Genomic Data

Authors:

Lorenzo Baldacci,

Matteo Golfarelli,

Simone Graziani,

Stefano RizziAuthors Info & Claims

DOLAP '14: Proceedings of the 17th International Workshop on Data Warehousing and OLAP

Pages 3 - 12

https://doi.org/10.1145/2666158.2666175

Published: 07 November 2014 Publication History

Abstract

The emerging medical models aim at leveraging on high-throughput genome sequencing technologies to better target drugs to patients' personal profiles so as to increase their effectiveness. However, the huge amount of data made available by these technologies calls for sophisticated and automated analysis techniques. In this direction we present GOLAM, a framework for OLAP analysis and mining of matches between genomic regions extracted from ENCODE, a worldwide-available collection of shared genomic data. The goal of GOLAM is to overcome the current limitations of genome analysis methods, that are normally based on browsing. This is done by partially automating and speeding-up the analysis process on the one hand, by making it more flexible and introducing a multi-resolution view of data on the other. The framework has been partially implemented so far; in this paper we focus on conveying its potential and on describing its functional architecture and the underlying data models.

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Cited By

Baldacci LGolfarelli MGraziani SRizzi S(2017)QETL: An approach to on-demand ETL from non-owned data sourcesData & Knowledge Engineering10.1016/j.datak.2017.09.002112(17-37)Online publication date: Nov-2017
https://doi.org/10.1016/j.datak.2017.09.002
Tradigo GCristiano FAlcaro SGreco SPollastri GVeltri PProsperi M(2016)G-quadruplex Structure Prediction and integration in the GenData2020 data modelProceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2975167.2985692(663-670)Online publication date: 2-Oct-2016
https://dl.acm.org/doi/10.1145/2975167.2985692

Index Terms

GOLAM: A Framework for Analyzing Genomic Data
1. Applied computing
  1. Operations research
    1. Decision analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems

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cover image ACM Conferences

DOLAP '14: Proceedings of the 17th International Workshop on Data Warehousing and OLAP

November 2014

110 pages

ISBN:9781450309998

DOI:10.1145/2666158

General Chair:
Il-Yeol Song
Drexel University, USA
,
Program Chairs:
Alkis Simitsis
HP Labs, USA
,
Alfredo Cuzzocrea
ICAR-CNR and University of Calabria, Italy

Copyright © 2014 ACM.

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Published: 07 November 2014

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Ministero dell'Istruzione, dell'Università e della Ricerca

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CIKM '14

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CIKM '14: 2014 ACM Conference on Information and Knowledge Management

November 7, 2014

Shanghai, China

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DOLAP '14 Paper Acceptance Rate 8 of 22 submissions, 36%;

Overall Acceptance Rate 29 of 79 submissions, 37%

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Cited By

Baldacci LGolfarelli MGraziani SRizzi S(2017)QETL: An approach to on-demand ETL from non-owned data sourcesData & Knowledge Engineering10.1016/j.datak.2017.09.002112(17-37)Online publication date: Nov-2017
https://doi.org/10.1016/j.datak.2017.09.002
Tradigo GCristiano FAlcaro SGreco SPollastri GVeltri PProsperi M(2016)G-quadruplex Structure Prediction and integration in the GenData2020 data modelProceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2975167.2985692(663-670)Online publication date: 2-Oct-2016
https://dl.acm.org/doi/10.1145/2975167.2985692

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