New Results
Toward A Scalable Exploratory Framework for Complex High-Dimensional Phenomics Data
Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy, Patrick Schnable
doi: https://doi.org/10.1101/159954
Methun Kamruzzaman
1School of Electrical Engineering & Computer Science, Pullman, WA, 99164, USA,
Ananth Kalyanaraman
2School of Electrical Engineering & Computer Science, Pullman, WA, 99164, USA,
Bala Krishnamoorthy
3Department of Mathematics and Statistics, Vancouver, WA, 98686, USA,
Patrick Schnable
4Department of Agronomy, Ames, IA, 50011, USA,
5Department of Genetics, Development and Cell Biology, Ames, IA, 50011, USA.
Article usage
Posted July 05, 2017.
Toward A Scalable Exploratory Framework for Complex High-Dimensional Phenomics Data
Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy, Patrick Schnable
bioRxiv 159954; doi: https://doi.org/10.1101/159954
Subject Area
Subject Areas
- Biochemistry (11703)
- Bioengineering (8722)
- Bioinformatics (29127)
- Biophysics (14932)
- Cancer Biology (12048)
- Cell Biology (17359)
- Clinical Trials (138)
- Developmental Biology (9406)
- Ecology (14143)
- Epidemiology (2067)
- Evolutionary Biology (18268)
- Genetics (12220)
- Genomics (16766)
- Immunology (11841)
- Microbiology (28005)
- Molecular Biology (11552)
- Neuroscience (60808)
- Paleontology (450)
- Pathology (1864)
- Pharmacology and Toxicology (3231)
- Physiology (4939)
- Plant Biology (10384)
- Synthetic Biology (2877)
- Systems Biology (7333)
- Zoology (1642)