NDLI: Designing Integrated Computational Biology Pipelines Visually

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A Recent Survey on Colon Cancer Detection Techniques

A Combination of Feature Extraction Methods with an Ensemble of Different Classifiers for Protein Structural Class Prediction Problem

Accuracy Guarantees for Phylogeny Reconstruction Algorithms Based on Balanced Minimum Evolution

Boolean Networks with Multiexpressions and Parameters

Comparison of Feature Selection Methods for Cross-Laboratory Microarray Analysis

Designing Integrated Computational Biology Pipelines Visually

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Generalized Query-Based Active Learning to Identify Differentially Methylated Regions in DNA

GenomeTools: A Comprehensive Software Library for Efficient Processing of Structured Genome Annotations

Hybrid Fuzzy Cluster Ensemble Framework for Tumor Clustering from Biomolecular Data

Inference of Gene Regulatory Networks with Variable Time Delay from Time-Series Microarray Data

Informative SNPs Selection Based on Two-Locus and Multilocus Linkage Disequilibrium: Criteria of Max-Correlation and Min-Redundancy

Modeling Associated Protein-DNA Pattern Discovery with Unified Scores

Multiobjective Identification of Controlling Areas in Neuronal Networks

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Protein Complex Prediction in Large Ontology Attributed Protein-Protein Interaction Networks

Reformulated Kemeny Optimal Aggregation with Application in Consensus Ranking of microRNA Targets

Sequence-Based Prediction of microRNA-Binding Residues in Proteins Using Cost-Sensitive Laplacian Support Vector Machines

Studying the Role of Lipid Rafts on Protein Receptor Bindings with Cellular Automata

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A New Approach to Implement Absorbing Boundary Condition in Biomolecular Electrostatics

Computer-Aided Biophysical Modeling: A Quantitative Approach to Complex Biological Systems

Quantitative Prediction of Peptide Binding to HLA-DP1 Protein

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Designing Integrated Computational Biology Pipelines Visually

Content Provider	IEEE Xplore Digital Library
Author	Jamil, H.M.
Copyright Year	2004
Abstract	The long-term cost of developing and maintaining a computational pipeline that depends upon data integration and sophisticated workflow logic is too high to even contemplate "what if" or ad hoc type queries. In this paper, we introduce a novel application building interface for computational biology research, called VizBuilder, by leveraging a recent query language called BioFlow for life sciences databases. Using VizBuilder, it is now possible to develop ad hoc complex computational biology applications at throw away costs. The underlying query language supports data integration and workflow construction almost transparently and fully automatically, using a best effort approach. Users express their application by drawing it with VizBuilder icons and connecting them in a meaningful way. Completed applications are compiled and translated as BioFlow queries for execution by the data management system LifeDB, for which VizBuilder serves as a front end. We discuss VizBuilder features and functionalities in the context of a real life application after we briefly introduce BioFlow. The architecture and design principles of VizBuilder are also discussed. Finally, we outline future extensions of VizBuilder. To our knowledge, VizBuilder is a unique system that allows visually designing computational biology pipelines involving distributed and heterogeneous resources in an ad hoc manner.
Sponsorship	IEEE Computer Society
Page Count	14
File Size	2060424
Starting Page	605
Ending Page	618
File Format	PDF
ISSN	15455963
Volume Number	10
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pipelines Data integration Computational biology Databases Visualization Object recognition Programming ad hoc queries visual programming ad hoc networks biological techniques biology computing data integration distributed databases query languages heterogeneous resources integrated computational biology pipeline workflow logic what if queries ad hoc type queries computational biology research query language life sciences databases ad hoc complex computational biology applications workflow construction VizBuilder icons BioFlow queries data management system LifeDB front end real life application distributed resources workflow computational pipelines systems biology
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Designing Integrated Computational Biology Pipelines Visually

A visual interface for on-the-fly biological database integration and workflow design using VizBuilder

Are Data Science Pipelines Fuzzy Queries?

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Optimizing Communications in Processing Data Integration Queries

Automatic example queries for ad hoc databases (2011)

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Automatic example queries for ad hoc databases

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Designing Integrated Computational Biology Pipelines Visually

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Designing Integrated Computational Biology Pipelines Visually

A visual interface for on-the-fly biological database integration and workflow design using VizBuilder

Are Data Science Pipelines Fuzzy Queries?

TableMaker: An ad hoc Query Tool for Relational Databases

Optimizing Communications in Processing Data Integration Queries

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