Collaborative Research: ABI Innovation

The overarching goal of the project is to design and develop a new scalable visual analytic software platform for phenomic datasets, in a way to elucidate the interplay among genotype (G) and environments (E) on phenotypes (P).

Software: A Scalable Framework for Visual Exploration and Hypotheses Extraction of Phenomics Data using TDA

Publications

Peer-review Publications (Accepted/in press/published)

  1. Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy, Stefan Hey, Patrick S. Schnable. "Hyppo-X: A Scalable Exploratory Framework for Analyzing Complex Phenomics Data" , ACM/IEEE Transactions on Computational Biology and Bioinformatics (TCBB) , Accepted/In Press, 2019, DOI: 10.1109/TCBB.2019.2947500
  2. Kaniz Madhobi, Methun Kamruzzaman, Ananth Kalyanaraman, Eric Lofgren, Rebekah Moehring, Bala Krishnamoorthy. "A visual analytics framework for analysis of patient trajectories" , Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB’19) , pp. 15-24, 2019. DOI: 10.1145/3307339.3342143.
  3. Meng Huang, Xiaolei Liu, Yao Zhou, Ryan M. Summers, and Zhiwu Zhang. "BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions" , GigaScience 8, no. 2 (2018): giy154. DOI: 10.1093/gigascience/giy154.
  4. Jiabo Wang, Zhengkui Zhou, Zhe Zhang, Hui Li, Di Liu, Qin Zhang, Peter J. Bradbury, Edward S. Buckler, Zhiwu Zhang. "Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits" , Heredity , vol. 121, pp. 648-662, 2018, DOI: 10.1038/s41437-018-0075-0.
  5. Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorhty. "Detecting divergent subpopulations in phenomics data using interesting flares" , Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB’18) , pp. 155-164, 2018. DOI: 10.1145/3233547.3233593.
  6. Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorhty. "Detecting divergent subpopulations in phenomics data using interesting flares" , Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB’18) , pp. 155-164, 2018. DOI: 10.1145/3233547.3233593.
  7. C. Tralie, N. Saul, and R. Barr-on. "Ripser.py. A Lean Persistent Homology Library for Python" , The Journal of Open Source Software , 3(29):925, 2018. DOI: 10.21105/joss.00925.
  8. L. McInnes, J. Healy, N. Saul, and L. Großerger. "UMAP: Uniform Manifold Approximation and Projection" , The Journal of Open Source Software , 3(29):861, 2018. DOI: 10.21105/joss.00861.
  9. E. Corbett, N. Saul, and M. Pirrung. "Interactive Machine Learning Heuristics in Learning from Users" , Workshop paper at IEEE Vis 2018 , Berlin, Germany, October 2018.
  10. Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy. "Characterizing the Role of Environment on Phenotypic Traits using Topological Data Analytics" , Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB'16) , pp. 487-488, 2016. DOI: 10.1145/2975167.2985646.

Manuscripts under review

  1. Ananth Kalyanaraman, Methun Kamruzzaman, Bala Krishnamoorthy. "Interesting paths in Mapper Complex" , Journal of Computational Geometry , under review, 2019.
  2. Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier. "The Relationship Between the Intrinsic Cech and Persistence Distortion Distances for Metric Graphs" , arXiv:1812.05282 , under review, 2019.
  3. Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier. "Local Versus Global Distances for Zigzag Persistence Modules" , arXiv:1903.08298 , under review, 2019.
  4. Matthew Broussard, Bala Krishnamoorthy, David Makin, Dale Willitts. "Topological Inference of Manifolds with Boundary" , , under review, 2019.
  5. Dustin Arendt, Matthew Broussard, Bala Krishnamoorthy, Nathaniel Saul. "Jaccard Filtration and Stable Paths in the Mapper" , arXiv: 1906.08256 , under review, 2019.
  6. Mustafa Hajij, Bei Wang, Paul Rosen. "MOG: Mapper on Graphs for Relationship Preserving Clustering" , arXiv:1804.11242 , under review, 2018.
  7. Yuan Wang, Bei Wang. "Topological Inference of Manifolds with Boundary" , arXiv:1810.05759 , under review, 2018.

Invited presentations

  1. Kaniz Madhobi, Methun Kamruzzaman, Ananth Kalyanaraman, Eric Lofgren, Rebekah Moehring, Bala Krishnamoorthy. "A visual analytics framework for analysis of patient trajectories" , ACM SIGKDD 2019 Workshop: epiDAMIK: Epidemiology meets Data Mining , 8 pages and invited presentation, 2019.
  2. N. Saul, and D. L. Arendt. "Explainable Machine Learning with Topological Data Analysis" , Demo in VISxAI Workshop at IEEE Vis 2018. Berlin, Germany, October 2018.

Professors

Ananth Kalyanaraman

Ananth Kalyanaraman

Professor

School of EECS

WSU

Bala Krishnamoorthy

Bala Krishnamoorthy

Professor

Department of Mathematics and Statistics

WSU, Vancouver

Bei Wang Phillips

Bei Wang Phillips

Assistant Professor

School of Computing

University of Utah

Larry Holder

Larry Holder

Professor

School of EECS

WSU

Patrick Schnable

Patrick Schnable

Professor

Department of Agronomy

Iowa State University

Zhiwu Zhang

Zhiwu Zhang

Associate Professor

Department of Crop and Soil Science

WSU

Students

Haixiao Dong

Haixiao Dong

Research scholar

Statistical Genetics

WSU

Kaniz Fatema Madhobi

Kaniz Fatema Madhobi

Ph.D. candidate

Computer Science

WSU

Methun Kamruzzaman

Methun Kamruzzaman

Ph.D. candidate

Computer Science

WSU

Matthew S. Broussard

Matthew S. Broussard

Ph.D. student

Mathematics

WSU

Alumni

Nathaniel Saul

Nathaniel Saul

Ph.D.

Mathematics

WSU Vancouver

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