Publications

Student co-authors are underlined.

Journal Publications (peer-reviewed)

  • Murph A, Flynt A, King BR. Comparing finite sequences of discrete events with non-uniform time intervals. Sequential Analysis 291–313 (2021) [DOI]
  • Kim T, King BR. Time series prediction using deep echo state networks. Neural Computing & Applications (2020) [DOI]
  • Hare-Harris AE, Mitchell MW, Meyers SM, Mitchel A, King BR, Ruocco B, Martin CL, Flax JF, Brzustowicz LM. Within-task variability on standardized language tests predicts autism spectrum disorder: A pilot study of the Response Dispersion Index. Journal of Neurodevelopmental Disorders 11:21 (2019) [DOI]
  • Lipsky E, King BR, Tromp G. Node-Oriented Workflow (NOW) – A command template workflow management tool for high throughput data analysis pipelines. Journal of Data Mining in Genomics and Proteomics 5(2) (2014) [DOI]
  • King BR, Aburdene M, Thompson A, Warres Z. Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity. EURASIP Journal on Bioinformatics and Systems Biology 2014:8 (2014) [DOI] [PDF]
  • Srinivasan SM, Vural S, King BR, Guda C. Mining for class-specific motifs in protein sequence classification. BMC Bioinformatics 14(96) (2013) [link]
  • King BR, Vural S, Pandey S, Barteau A, Guda C. ngLOC: software and web server for predicting protein subcellular localization in prokaryotes and eukaryotes. BMC Research Notes 5(351) (2012) [link] [PDF]
  • Guda C, King BR, Pal LR, Guda P. A top-down approach to infer and compare domain-domain interactions across eight model organisms. PLoS One 4(3) (2009) [DOI]
  • King BR, Latham L, Guda C. Estimating the subcellular proteome of prokaryotes. The Open Applied Informatics Journal 3(1) (2009) [PDF]
  • King BR, Guda C. Semi-supervised learning for classification of protein sequence data. Scientific Programming 16(1) (2008) [DOI]
  • King BR, Guda C. ngLOC: an n-gram based Bayesian method for estimating the subcellular proteomes of eukaryotes. Genome Biology 8(5):R68 (2007) [DOI]

International Conferences (peer-reviewed)

  • Collins DB, Barnhart S, King BR, Koranteng S, Lourderaj I, McGuire C, Spang Z, Tuffour S, Dutcher DD. Spatial Analysis and Source-Investigation of Aerosols in a Legacy Anthracite Coal Region (Shamokin, PA). AAAR 44th Annual Conference, October 26–30, Pasadena, CA, USA (Poster) [link]
    • Presented by D. D. Dutcher. From our community air-quality sensor network in the Shamokin coal region; my part is the data pipeline and quality-control software, with undergraduate researchers.
  • Mattucci P, Snyder R, King BR, Dutcher DD, Raymond TM. Suberic Acid: Discovery of a Gamma Polymorph. AIChE 2026 Annual Meeting, Annual Student Conference, November 9, Minneapolis, MN, USA (Poster) [link]
  • Grable C, Snyder R, Dutcher DD, Raymond TM, King BR, Burek V. The Effects of Droplet Concentration on Polymorphs of Aerosolized Glutaric Acid in IPA. AIChE 2026 Annual Meeting, Annual Student Conference, November 9, Minneapolis, MN, USA (Poster) [link]
  • Collins DB, Dutcher DD, Barnhart S, King BR, Koranteng S, Lourderaj I, McGuire C, Spang Z, Tuffour S. Air Quality in a Rural Anthracite Coal Region of Pennsylvania. AAAR 44th Annual Conference, October 26–30, Pasadena, CA, USA (Talk) [link]
    • Presented by D. B. Collins.
  • King BR, Talmage E. Nifty: DNA Sequence Matching. ACM SIGCSE Technical Symposium 2026: Nifty Assignments, February 18–21, St. Louis, Missouri, USA [link]
  • Zeng Z, Raymond T, Dutcher D, King BR. Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) Design for Aerosol Mixture Hygroscopic Behavior Studies. AIChE 2022 Annual Meeting, Nov 13–18, Phoenix, AZ, USA [link]
  • Zeng Z, Hatzinger B, Torres G, Dutcher D, Raymond T, King BR. On the Development and Setup of a Hygroscopic Tandem Differential Mobility Analyzer for Aerosol Studies. AIChE 2021 Annual Meeting, Nov 7–11, Boston, MA, USA [link]
  • Murph A, Flynt A, King BR. Comparing finite sequences of discrete events with non-uniform time intervals. CS2021: The Classification Society Annual Meeting, Nov 5–7, Lewisburg, PA, USA [link]
  • Pirmann C, Acharya B, King BR, Faull K. Training Algorithms to Read Complex Collections: Handwriting Classification for Improved HTR Models. DH2020: Digital Humanities, July 22–24, Ottawa, Canada [link]
    • Presented remotely due to the COVID-19 pandemic
  • King BR, Troiani V. Identifying Scanpath Trends using a Frequent Trajectory Pattern Mining Approach. VSS19: Vision Sciences Society 19th Annual Meeting, St. Pete Beach, FL, May 17–22, 2019. Journal of Vision 19(10), 307a [DOI]
  • Hare-Harris AE, Mitchel MW, King BR, Myers SM, Greene B, Martin CL, Flax JF, Brzustowicz LM. Developmental Deviance of Item-Level Responses on Standardized Language Measures Correlates with Autism Spectrum Disorder Diagnosis. International Meeting for Autism Research, IMFAR 2016, May 11–14, Baltimore, MD [link]
  • Hare-Harris AE, King BR, Essae E, Ledbetter DH, Martin CL. Assessing the pathogenicity of novel CNVs in cases through the use of dosage sensitivity maps of copy number variants in a large control population. ASHG 2015: American Society of Human Genetics, Oct 6–10, Baltimore, MD [link]
    • Reviewer’s Choice Abstract winner (top 10% of 3,258 abstracts); #24 in People’s Choice ranking
  • Ren C, King BR. Predicting Protein Contact Maps by Bagging Decision Trees. Proceedings of BCB ’14: ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Sept 20–23, Newport Beach, CA [link] [PDF]
  • Hofmeister B, King BR. ngPhylo – N-gram Modeled Proteins with Substitution Matrices for Phylogenetic Analysis. Proceedings of BCB ’13: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine, Sept 22–25, Washington DC [link] [PDF]
  • Cole C, King BR. Using Machine Learning to Predict the Health of HIV-Infected Patients. Proceedings of BCB ’13: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine, Sept 22–25, Washington DC [link] [PDF]
  • King BR, Satyanarayana A. Teaching Data Mining in the Era of Big Data. American Society for Engineering Education, ASEE 2013, June 23–26, Atlanta, GA [link] [PDF]
  • Segar M, King BR. An n-gram based probabilistic method for de novo sequence assembly. 20th Annual International Conference on Intelligent Systems for Molecular Biology, ISMB 2012, July 15–17, Long Beach, CA (Poster) [PDF]
  • King BR, Guda C. Semi-supervised learning for protein classification. ROCKY 07 – 5th Annual Rocky Mountain Bioinformatics Conference, November 30 – December 2, 2007, Aspen, CO [link]

Local and Regional Conferences

  • Gunn Cheu J, Hendrix A, Field K, King BR. Immunoglobulin Gene Annotation Refinement using Machine Learning Classifiers. 25th Annual Kalman Research Symposium, April 11, 2026, Bucknell University, Lewisburg, PA (Talk) [link]
  • Sharma K, King BR. Trajectory Gaze Path Analysis and Isolating Areas of Interest in Eye-Tracking Data for Autism Spectrum Disorder Studies. 21st Annual Kalman Research Symposium, April 9, 2022, Bucknell University, Lewisburg, PA (Poster)
  • Sharma K, King BR, Troiani V. Trajectory Gaze Path Analysis and Isolating Areas of Interest in Eye-Tracking Data for Autism Spectrum Disorder Studies. Susquehanna Valley Undergraduate Research Symposium, SVURS 2021 (virtual), July 2021 (Poster)
  • Pirmann CM, King BR, Acharya B, Faull K. Collaborating on Machine Reading: Training Algorithms to Read Complex Collections. Bucknell University Digital Scholarship Conference, BUDSC19, Oct 11–13, Bucknell University, Lewisburg, PA (Talk)
  • Yang T, Troiani V, King BR. Using Deep Learning to Analyze Images That Have High Interest from Children with Autism. 16th Annual Kalman Research Symposium, April 1, 2017, Bucknell University, Lewisburg, PA (Poster)
  • Eckenroth M, Troiani V, King BR. Assessing the Utility of Virtual Reality on Selective Attention Bias in Children with Autism Spectrum Disorder. 6th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2016, July 29, Bloomsburg University, Bloomsburg, PA (Poster)
  • Yang T, Troiani V, King BR. Using Deep Learning to Analyze Images That Have High Interest from Children with Autism. 6th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2016, July 29, Bloomsburg University, Bloomsburg, PA (Poster)
  • Yang T, Troiani V, King BR. Using Deep Learning to Analyze Images That Have High Interest from Children with Autism. Sigma Xi Summer Research Symposium 2016, July 21, Bucknell University, Lewisburg, PA (Poster)
  • Pham S, King BR. Using Machine Learning to Automatically Predict Feature Representation on Sequential Data. 15th Annual Kalman Research Symposium, April 2, 2016, Bucknell University, Lewisburg, PA (Poster)
  • Hammett J, King BR. Using Data Mining to Construct More Practical Weather Forecasting Models. 15th Annual Kalman Research Symposium, April 2, 2016, Bucknell University, Lewisburg, PA (Poster)
  • Cowen R, Mitchel M, Hare-Harris AE, King BR. Application of n-gram prediction and Brown’s Stages of Syntactic and Morphological Development to design augmentative and alternative communication for children with autism. 5th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2015, August 4, Bucknell University, Lewisburg, PA (Poster)
  • Pham S, King BR. Using Deep Learning to Automatically Learn Feature Representation and Build a Better Classification Model on Protein Sequential Data. 5th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2015, August 4, Bucknell University, Lewisburg, PA (Poster)
  • Hammett J, King BR. Using Data Mining to Construct More Practical Weather Forecasting Models. Sigma Xi Summer Research Symposium 2015, July 23, Bucknell University, Lewisburg, PA (Poster)
  • Rogge M, King BR. Analysis of Spike Timing Dependent Neural Networks for More Efficient Starting State Learning. 14th Annual Kalman Research Symposium, March 28, 2015, Bucknell University, Lewisburg, PA
  • Gonthier S, King BR. Using statistical learning to improve word prediction for augmentative and alternative communication. 14th Annual Kalman Research Symposium, March 28, 2015, Bucknell University, Lewisburg, PA
  • Ren C, King BR. Predicting a protein contact map from protein sequence. 4th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2014, August 5, Geisinger Research, Danville, PA
  • Gonthier S, King BR. Using statistical learning to improve word prediction for augmentative and alternative communication. 4th Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2014, August 5, Geisinger Research, Danville, PA
    • Winner for oral presentation – one of three chosen out of 86 submissions
  • Gonthier S, King BR. Using statistical learning to improve word prediction for augmentative and alternative communication. Sigma Xi Summer Research Symposium, July 24, 2014, Bucknell University, Lewisburg, PA
  • Ren C, King BR. An improved method for protein contact map prediction. 13th Annual Kalman Research Symposium 2014, March 29, Bucknell University, Lewisburg, PA
  • Dwornik L, King BR. Regular expressions for named entity recognition. 13th Annual Kalman Research Symposium 2014, March 29, Bucknell University, Lewisburg, PA
  • Cole C, King BR. Using Machine Learning to Predict the Health of HIV-Infected Patients. Third Annual Susquehanna Valley Undergraduate Research Symposium, SVURS 2013, August 6, Geisinger Research, Danville, PA [PDF]
    • Winner for oral presentation – one of three chosen out of 67 submissions
  • Cole C, King BR. Identification of Genetic Variance in HIV Associated with Varying Stages of AIDS to Assess a Patient’s Prognosis. 12th Annual Kalman Research Symposium 2013, April 13, Bucknell University, Lewisburg, PA
  • Segar M, King BR. Genome Assembly from Next Generation Sequencing Instrumentation. Susquehanna Valley Undergraduate Research Symposium, August 9, 2011, Geisinger Research, Danville, PA
  • Stahlfeld P, Tromp G, King BR. Installation and deployment of caBIG for cancer research. Sigma Xi Summer Research Symposium, July 27, 2011, Bucknell University, Lewisburg, PA
  • Segar M, King BR. Genome Assembly from Next Generation Sequencing Instrumentation. Sigma Xi Summer Research Symposium, July 27, 2011, Bucknell University, Lewisburg, PA
  • King BR, Barteau A, Guda C. ngLOC: software for proteome-wide prediction of subcellular localization. Sigma Xi Summer Research Symposium, July 27, 2011, Bucknell University, Lewisburg, PA
  • Kagle J, King BR. Identification of a Putative Chlorocatechol Catabolic Pathway in the Triclosan Degrader Sphingomonas sp. RD1. NEMPET 2010, June 25–27, 2010, Blue Mountain Lake, NY (Poster) [PDF]

Honors Theses Advised

  • Ryan Koes — Deep Learning Approaches for Voltammetric Analysis of Coffee. Bucknell University Honors Thesis, 2026 (co-advisor)
  • Sean O’Connor — A Web-Based Wizard-of-Oz Platform for Collaborative and Reproducible Human-Robot Interaction Research. Bucknell University Honors Thesis, 2026 (second reader)
  • Taehwan Kim ’20 — Chaotic Time Series Prediction using Deep Echo State Networks. Bucknell University Honors Thesis, 2020
  • Chuqiao Ren ’15 — Predicting Protein Contact Maps by Bagging Decision Trees. Bucknell University Honors Thesis, 2015
  • Charles Cole ’14 — Using Machine Learning to Predict the Health of HIV-Infected Patients. Bucknell University Honors Thesis, 2014
  • Matthew Segar ’12 — Utilization of Probabilistic Models in Short Read Assembly from Second-Generation Sequencing. Bucknell University Honors Thesis, 2012 [PDF]
    • Winner of the Harold W. Miller Prize for Outstanding Honors Thesis

Dissertation

  • King BR. Protein Sequence Classification with Bayesian Supervised and Semi-Supervised Learned Classifiers. PhD dissertation, University at Albany, State University of New York, 2008 [PDF]
    • Distinguished Doctoral Dissertation Award, University at Albany, 2008

Invited talks and panels are listed on Talks, Panels & Workshops.

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