Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Kaitoua A"'
Publikováno v:
In Methods 1 December 2016 111:3-11
Publikováno v:
it - Information Technology. 62:145-156
There is an increasing interest in fusing data from heterogeneous sources. Combining data sources increases the utility of existing datasets, generating new information and creating services of higher quality. A central issue in working with heteroge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c2635b073afe3758145e685601abdce
https://doi.org/10.1515/itit-2019-0037
https://doi.org/10.1515/itit-2019-0037
Autor:
Mageda Sharafeddin, Hazem Hajj, Mazen A. R. Saghir, Hassan Artail, Abdulrahman Kaitoua, Raghid Morcel, Haitham Akkary
Publikováno v:
IEEE Transactions on Cloud Computing. 7:850-865
While cloud computing has provided major benefits by maximizing the use of resources within a cloud, the current solutions still face many challenges. In this paper, we propose performance enhancements for cloud computations, provided by integrating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0935fc0f28e9a032b881beef072b9f5a
https://doi.org/10.1109/tcc.2017.2665493
https://doi.org/10.1109/tcc.2017.2665493
Publikováno v:
IEEE Transactions on Computers
Genome sequencing is expected to be the most prolific source of big data in the next decade; millions of whole genome datasets will open new opportunities for biological research and personalized medicine. Genome sequences are abstracted in the form
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47544011a91d5efe9d3df1959eb9cf74
https://doi.org/10.1109/tc.2018.2854880
https://doi.org/10.1109/tc.2018.2854880
Publikováno v:
ICDE
With the huge growth of genomic data, exposing multiple heterogeneous features of genomic regions for millions of individuals, we increasingly need to support domain-specific query languages and knowledge extraction operations, capable of aggregating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55206e9ff654b8983b20963e053304ce
https://doi.org/10.1109/icde48307.2020.00017
https://doi.org/10.1109/icde48307.2020.00017
Autor:
Luca Nanni, Marco Masseroli, Pietro Pinoli, Anna Bernasconi, Abdulrahman Kaitoua, Olha Horlova, Stefano Ceri, Eirini Stamoulakatou, Stefano Perna, Andrea Gulino, Arif Canakoglu
Publikováno v:
Bioinformatics
Motivation We previously proposed a paradigm shift in genomic data management, based on the Genomic Data Model (GDM) for mediating existing data formats and on the GenoMetric Query Language (GMQL) for supporting, at a high level of abstraction, data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cc43a1cb92056f8cdb458cb5d3a7e68
https://doi.org/10.1093/bioinformatics/bty688
https://doi.org/10.1093/bioinformatics/bty688
Publikováno v:
ICDE
Large datasets can originate from various sources and are being stored in heterogeneous formats, schemas, and locations. Typical data science tasks need to combine those datasets in order to increase their value and extract knowledge. This is done in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2884af251ddcf0f687b82aa9eeebec51
https://doi.org/10.1109/icde.2019.00152
https://doi.org/10.1109/icde.2019.00152
Publikováno v:
ICDE
In previous work, we presented GenoMetric Query Language (GMQL), an algebraic language for querying genomic datasets, supported by Genomic Data Management System (GDMS), an open-source big data engine implemented on top of Apache Spark. GMQL datasets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b94298328a99c48528d4bc03c905776
https://doi.org/10.1109/icde.2019.00107
https://doi.org/10.1109/icde.2019.00107
Autor:
Pietro Pinoli, Abdulrahman Kaitoua, Marco Masseroli, Stefano Ceri, Luca Nanni, Arif Canakoglu, Andrea Gulino
Publikováno v:
CIKM
In the last ten years, genomic computing has made gigantic steps due to Next Generation Sequencing (NGS), a high-throughput, massively parallel technology; the cost of producing a complete human sequence dropped to 1000 US$ in 2015 and is expected to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b18f86296af7f72f31094fb874c6498
https://doi.org/10.1145/3269206.3269217
https://doi.org/10.1145/3269206.3269217
Autor:
Luca Nanni, Pietro Pinoli, Anna Bernasconi, Andrea Gulino, Arif Canakoglu, Stefano Ceri, Marco Masseroli, Abdulrahman Kaitoua
Publikováno v:
Communications in Computer and Information Science
Communications in Computer and Information Science-Data Analytics and Management in Data Intensive Domains
Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2017
Communications in Computer and Information Science ISBN: 9783319965529
DAMDID/RCDL (Selected Papers)
Communications in Computer and Information Science-Data Analytics and Management in Data Intensive Domains
Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2017
Communications in Computer and Information Science ISBN: 9783319965529
DAMDID/RCDL (Selected Papers)
Next Generation Sequencing is a 10-year old technology for reading the DNA, capable of producing massive amounts of genomic data - in turn, reshaping genomic computing. In particular, tertiary data analysis is concerned with the integration of hetero
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::093a69d682f4fa0a043af3763b6c7781
http://hdl.handle.net/11311/1058981
http://hdl.handle.net/11311/1058981
