PIPages
Labs

Arjun Krishnan

University of Colorado Denver/Anschutz Medical Campus, CO·Plant Science & Agriculture

Biologists can read an organism's whole genome, but cannot yet measure an organism's full form with similar completeness. Predicting what an organism looks like from its genes is one of biology's grand challenges.

Fields

Plant Science & Agriculture

Computer Science

Mathematics & Statistics

Topics

topological data analysis

Euler Characteristic Transform

Mapper algorithm

Grants
1 known grant, through Jun 2027

What they work on

  1. Measure the total information in Arabidopsis leaf shape from X-ray CT scans using the Euler Characteristic Transform, and compare it with traditional shape measures to reveal hidden trait information.
  2. Generate RNA-seq gene expression profiles from the same leaves and summarize gene expression and shape data as graphs using the Mapper topological data analysis algorithm.
  3. Predict specific leaf shape features from gene expression signatures by aligning molecular and shape Mapper graphs with an encoder-decoder deep learning network.
  4. Train U.S. and Mexican students to analyze project data through Plants&Python, a free bilingual curriculum that teaches coding to plant biologists.

More about the research

This collaborative project tackles it with topological data analysis (TDA), a branch of mathematics that measures the shape and structure of data. It uses leaves of Arabidopsis, a small model plant, as the test case.

Why it matters

Linking gene activity to precise physical traits could eventually help plant scientists and breeders predict crop traits from molecular data. The project's methods for measuring complex shapes from images, and its public datasets, could be reused for other plant traits. The bilingual Plants&Python curriculum trains students across the U.S. and México in coding for plant biology.

Known grants

From NIH and NSF research grants. Labs often have other funding we can't see.

Collaborative Research: RESEARCH-PGR: Predicting Phenotype from Molecular Profiles with Deep Learning: Topological Data Analysis to Address a Grand Challenge in the Plant Sciences

NSF · Jul 2023 – Jun 2027

Closest labs

Brittany Fasy

Montana State University, MT·Mathematics & Statistics·Early-career

Quantify how well topological transforms, families of descriptors such as persistence diagrams or Euler characteristic curves computed over many directions or subspaces, represent a topological space.

Tao Hou

University of Oregon, OR·Computer Science

Devise efficient algorithms and new data structures for computing representatives, the concrete cycles in a dataset that realize each feature found by persistent homology, a tool tracking holes and loops across scales.

Chul Moon

Southern Methodist University, TX·Mathematics & Statistics

Develop methods that pair a tumor's location with its topological shape features in three-dimensional MRI scans of gliomas, and test how these features relate to the tumors' genomic characteristics.

The school

University of Colorado Denver/Anschutz Medical Campus: 41 labs on PI Pages, $766M a year on research, 205 research doctorates a year.

More about University of Colorado Denver/Anschutz Medical Campus

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