Efficient Techniques to Explore and Rank Paths in Life Science Data Sources

Lacroix, Zoé; Raschid, Louiqa; Vidal, María-Esther

doi:10.1007/978-3-540-24745-6_13

Cited by 23 publications

(25 citation statements)

References 8 publications

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“…To have more control over the resulting paths, we need a query language that allows an investigator to specify the path types of interest. Earlier suggestions for query languages for paths include regular expressions [15] and context-free grammars [16]. Expressive query languages open possibilities for specifying aspects such as the formulae for degree penalties as background knowledge, or edge relevances, that could be made context sensitive.…”

Section: Discussionmentioning

confidence: 99%

Link Discovery in Graphs Derived from Biological Databases

Sevon

Eronen

Hintsanen

et al. 2006

Lecture Notes in Computer Science

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Abstract. Public biological databases contain vast amounts of rich data that can also be used to create and evaluate new biological hypothesis. We propose a method for link discovery in biological databases, i.e., for prediction and evaluation of implicit or previously unknown connections between biological entities and concepts. In our framework, information extracted from available databases is represented as a graph, where vertices correspond to entities and concepts, and edges represent known, annotated relationships between vertices. A link, an (implicit and possibly unknown) relation between two entities is manifested as a path or a subgraph connecting the corresponding vertices. We propose measures for link goodness that are based on three factors: edge reliability, relevance, and rarity. We handle these factors with a proper probabilistic interpretation. We give practical methods for finding and evaluating links in large graphs and report experimental results with Alzheimer genes and protein interactions.

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Section: Discussionmentioning

confidence: 99%

Link Discovery in Graphs Derived from Biological Databases

Sevon

Eronen

Hintsanen

et al. 2006

Lecture Notes in Computer Science

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“…A questionnaire was developed based on lists of user requirements in three kinds of documents: (i) survey articles [11] and reports of workshops on biological source querying (ii) studies on data quality [14], [4], [15] and (iii) studies on user guidance during the querying process, involving BioMediator [12], BioNavigation [9] and DSS [2]. The questionnaire comprised 28 questions and was constructed according to standard guidelines.…”

Section: Process: Interviews and Questionnairementioning

confidence: 99%

“…an estimate of the number of instances of an entity in a source) [9]. These initial values may then be improved, adjusted or rectified by comparing the values obtained for all the source-entities related to a given set of entities and/or to a given set of sources.…”

Section: Initializing Preferencesmentioning

confidence: 99%

“…If the number of alternative paths is still too large, we can sort them according to the biologist's preferences [2], [9]. To do this, we must associate a value with each path.…”

Section: Using Values Of Preferencesmentioning

confidence: 99%

“…We sum-up the differences between our approach and these works. Firstly, the underlying query languages of [9] and [12] [13] are formal query languages: a regular expressions based query language and an XML-based path language called PQL, respectively. Following our user-centric approach we have proposed a user-friendly graphical query language.…”

Section: Example Of Cgh Analysismentioning

confidence: 99%

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A User-Centric Framework for Accessing Biological Sources and Tools

Cohen-Boulakia

Davidson

Froidevaux

2005

Lecture Notes in Computer Science

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Biologists face two problems in interpreting their experiments: the integration of their data with information from multiple heterogeneous sources and data analysis with bioinformatics tools. It is difficult for scientists to choose between the numerous sources and tools without assistance. Following a thorough analysis of scientists' needs during the querying process, we found that biologists express preferences concerning the sources to be queried and the tools to be used. Interviews also showed that the querying process itself -the strategy followed -differs between scientists. In response to these findings, we have introduced a user-centric framework allowing to specify various querying processes. Then we have developed the BioGuide system which helps the scientists to choose suitable sources and tools, find complementary information in sources, and deal with divergent data. It is generic in that it can be adapted by each user to provide answers respecting his/her preferences, and obtained following his/her strategies. Abstract. Biologists face two problems in interpreting their experiments: the integration of their data with information from multiple heterogeneous sources and data analysis with bioinformatics tools. It is difficult for scientists to choose between the numerous sources and tools without assistance. Following a thorough analysis of scientists' needs during the querying process, we found that biologists express preferences concerning the sources to be queried and the tools to be used. Interviews also showed that the querying process itself -the strategy followed -differs between scientists. In response to these findings, we have introduced a user-centric framework allowing to specify various querying processes. Then we have developed the BioGuide system which helps the scientists to choose suitable sources and tools, find complementary information in sources, and deal with divergent data. It is generic in that it can be adapted by each user to provide answers respecting his/her preferences, and obtained following his/her strategies.

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