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Name
BieColl - Bielefeld Electronic Collections
Type
Institutional Repository
Items
786 Publications
Compatibility
OpenAIRE Basic (DRIVER OA)
OAI-PMH
http://biecoll.ub.uni-bielefeld.de/oai2/oai2.php
More information
Detailed data provider information (OpenDOAR)

 

  • Genlight: Interactive high-throughput sequence analysis and comparative genomics

    With rising numbers of fully sequenced genomes the importance of comparative genomics is constantly increasing. Although several software systems for genome comparison analyses do exist, their functionality and flexibility is still limited, compared to the manifold possible applications. Therefore, we developed Genlight, a Client/Server based program suite for large scale sequence analysis and comparative genomics. Genlight uses the object relational database system PostgreSQL together with a...

    BRIL - Capturing Experiments in the Wild

    This presentation describes a project to embed a repository system (based on Fedora) within the complex, experimental processes of a number of researchers in biophysics and structural biology. The project is capturing not just individual datasets but entire experimental workflows as complex objects, incorporating provenance information based on the Open Provenance Model, to support reproduction and validation of published results. The repository is integrated within these experimental proces...

    Self-Organized Ordering of Terms and Documents in NSF Awards Data

    We present the results of an analysis of a text corpus of 129,000 abstracts of NSF-sponsored basic research projects between years 1990 and 2003. The methods used in the analysis include term extraction based on a reference corpus and an entropy measure, and the Self-Organizing Map algorithm for the formation of a term map and a document map. Methodologically, the basic approach is based on earlier developments, such as word category maps and the WEBSOM method, but in the level of details, we...

    A Three-Level Computational Attention Model

    This article deals with a biologically-motivated three-level computational attention model architecture based on the rarity and the information theory framework. It mainly focuses on a low-level step which aims in fastly highlighting important areas and a middle-level step which analyses the behaviour of the detected areas. Their application on both still images and videos provide results to be used by the third high-level step.
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