Data Mining in Life Sciences: A Case Study on SAPs In-Memory Computing Engine

Autor:	Matthias Steinbrecher, Massimiliano Marcon, Miganoush Katrin Magarian, Cafer Tosun, Joos-Hendrik Boese, Gennadi Rabinovitch, Vishal Sikka
Rok vydání:	2013
Předmět:	Computer science business.industry Data management Online analytical processing InformationSystems_DATABASEMANAGEMENT Analysis models computer.software_genre Pipeline (software) Data science Toolbox In-Memory Processing Business intelligence Data mining business computer
Zdroj:	Lecture Notes in Business Information Processing ISBN: 9783642398711 BIRTE
DOI:	10.1007/978-3-642-39872-8_2
Popis:	While column-oriented in-memory databases have been primarily designed to support fast OLAP queries and business intelligence applications, their analytical performance makes them a promising platform for data mining tasks found in life sciences. One such system is the HANA database, SAP’s in-memory data management solution. In this contribution, we show how HANA meets some inherent requirements of data mining in life sciences. Furthermore, we conducted a case study in the area of proteomics research. As part of this study, we implemented a proteomics analysis pipeline in HANA. We also implemented a flexible data analysis toolbox that can be used by life sciences researchers to easily design and evaluate their analysis models.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8baa1fea436483155da9a7653f2dd015 https://doi.org/10.1007/978-3-642-39872-8_2 Zobrazit plný text záznamu