BING: Biomedical informatics pipeline for Next Generation Sequencing

Jeffrey Kriseman, Christopher Busick, Szabolcs Szelinger, Valentin Dinu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


High throughput parallel genomic sequencing (Next Generation Sequencing, NGS) shifts the bottleneck in sequencing processes from experimental data production to computationally intensive informatics-based data analysis. This manuscript introduces a biomedical informatics pipeline (BING) for the analysis of NGS data that offers several novel computational approaches to 1. image alignment, 2. signal correlation, compensation, separation, and pixel-based cluster registration, 3. signal measurement and base calling, 4. quality control and accuracy measurement. These approaches address many of the informatics challenges, including image processing, computational performance, and accuracy. These new algorithms are benchmarked against the Illumina Genome Analysis Pipeline. BING is the one of the first software tools to perform pixel-based analysis of NGS data. When compared to the Illumina informatics tool, BING's pixel-based approach produces a significant increase in the number of sequence reads, while reducing the computational time per experiment and error rate (<2%). This approach has the potential of increasing the density and throughput of NGS technologies.

Original languageEnglish (US)
Pages (from-to)428-434
Number of pages7
JournalJournal of Biomedical Informatics
Issue number3
StatePublished - Jun 2010


  • Analysis
  • Base calling
  • DNA sequencing
  • Image alignment
  • Image analysis
  • Image processing
  • Next Generation Sequencing
  • Signal processing
  • Software

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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