Implementing computational biology pipelines using VisFlow

Mou, Xin; Jamil, Hasan M.; Rinker, Robert

doi:10.1504/ijdmb.2017.084262

Cited by 3 publications

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“…In our own lab, we are focused on developing smart declarative querying and workflow engines for distributed and heterogenous scientific databases. We have developed a declarative query language for data integration called BioFlow [38,39] based on which we have developed two visual interfaces called VizBuilder [33,28] and VisFlow [55,53,54] to support distributed workflow queries for Life Sciences data management and querying system called the LifeDB [9]. To complement LifeDB, we have also develop an ID mapping database called the MapBase [35] and phylogenetic database PhyloBase [37,36].…”

Section: Related Researchmentioning

confidence: 99%

Knowledge Rich Natural Language Queries over Structured Biological Databases

Jamil

2017

Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics

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Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made.

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