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Exploring the Algorithms of Life

Exploring the Algorithms of Life

Thanks to Phil Bogdan, Marketing and Communications Manager for the Office of Research and Economic Development, for helping us tell our story. This article was published in the November 2019 Scholars and Researchers newsletter. Tawny is just one of the amazing students we have working on the various research projects within IMCI. Professor Marty Yterberg is the Associate Director of IMCI and PI on the RII Track-2 FEC: Using Biophysical Protein Models to Map Genetic Variation to Phenotypes.


Scientists call proteins coded by DNA ‘the building blocks of life.’ For Tawny Gonzalez, these proteins became building blocks for her education.

Gonzalez, an alumna of the College of Science and first-year WWAMI medical student, plays a key role in a molecular modeling study using complex math to plot out the genetic changes affecting the health and structure of living things.

Gonzalez indirectly found her interest in molecular modeling while shadowing an infectious disease physician at Kootenai Health in Coeur d’Alene.

“That was the coolest shadow job, true Sherlock Holmes stuff,” Gonzalez said. “To diagnose culprits for infection, you have to follow clues in the patient’s body and history to figure out when and where they were exposed,” Gonzalez said.

Gonzalez began exploring ways to research viruses and infectious diseases at U of I. While looking into projects in the physics department, she learned about Marty Ytreberg, professor of physics and an associate director of U of I’s Institute for Modeling Collaboration and Innovation (IMCI), a highly collaborative center that teams up with researchers to integrate more modeling into their projects.

Ytreberg, a biophysicist by training, recently published a paper with colleagues about using computational methods to help predict whether mutations in the Ebola virus could weaken treatment efforts.

“I was fascinated by the idea that physics could be so deeply involved in biology,” Gonzalez said. “I had no idea what molecular modeling was, how computational methods worked, or how I would fit into his research group; but I thought it would be interesting. I decided to see if Marty would let me join the group despite my lack of knowledge.”

Even with the steep learning curve, Gonzalez joined Ytreberg’s IMCI working group, using molecular modeling to benefit human health. She quickly picked up the basics and found herself exploring the complex math and algorithms that can make research more efficient and less costly.

“It was cool to see how physics could be used to predict biological interactions that could then assist people on the experimental side,” Gonzalez said.

As Gonzalez’s interest and knowledge in molecular modeling grew, Ytreberg brought her in to a project to understand how amino acid mutations in proteins change the way proteins fold and bind and in turn how this changes plant and animal characteristics. The project, led by Ytreberg, involved researchers from Idaho, Rhode Island and Vermont.

“Using computational methods to narrow down the number of mutations a research group should study can be very beneficial, but it’s difficult; there are a bunch of models out there using different algorithms, and it’s not always clear which one would best suit a researcher’s needs,” Gonzalez said.

Gonzalez used special databases to thoroughly document the structure and binding strengths of various proteins, including those that result in notorious ailments like HIV, cancers and plagues. She used this database to test the speed and accuracy of eight computational methods that predict protein binding strength after mutations. In all, she tested 16 protein complexes involving two or more proteins interacting with each other.

Gonzalez originally believed that the more advanced calculations would be better at predicting final outcomes, but that wasn’t always the case.

“Many models did well at predicting how simpler proteins would bind and fold with other proteins,” Gonzalez said. “But some didn’t do as well, particularly in more complicated scenarios, like when viruses interact with antibodies.

Gonzalez and Ytreberg expanded their study to look at these more complex cases.

“We wanted to be able to suggest, ‘If you need a basic method for predicting a simple mutation, use this one. If you want to make predictions for a more complex scenario involving certain viral proteins and antibodies, this other method can work well.’”

Gonzalez’s work will be featured in a research paper that she and Ytreberg will soon submit for publication in a scientific journal.

“Tawny will be the first author on this paper, which is very unusual for an undergraduate student,” said Ytreberg. “She’s driven, motivated, self-sufficient, and capable of tackling tough projects alone. She’s really done the brunt of the work, and that’s very impressive for an undergrad working a handful of hours a week.”

Gonzalez graduated in May 2019 with a B.S. in chemistry and biochemistry, as well as a minor in physics. She plans to continue pursuing her interest in infectious disease through U of I’s WWAMI Medical Education Program. She also plans to earn a Master of Public Health degree before practicing medicine in Moscow.

“I want to be a real driver of public health in Idaho,” Gonzalez said. “Having an M.D. and a Master of Public Health degree can really help me do that!”

Data Carpentries Training

Data Carpentries Training

IMCI is sponsoring the University of Idaho as a member organization in The Carpentries training program to improve data literacy and reproducible science.

The Carpentries teaches foundational computational and data science skills to researchers worldwide. They train and certify volunteer instructors and provide curriculum in a variety of topics designed to be presented as workshops.

At the University of Idaho, graduate students and postdocs will run three 2-day workshops for anyone interested in learning practical data analysis skills. These workshops are open to upper-level undergraduate stdents, new graduate students, and anyone else interested in good-practices in data management and analysis.

STUDENTS can register for academic credit

Students wishing to take the workshops for credit need to register via the UI course schedule for any combination of BCB 503 01, BCB 503 02, and/or BCB 503 03. Each workshop is 1 credit each.

NON-STUDENTS must also register to attend

If you do not want academic credit, you may attend any workshop for free but must still register. Space is limited.


Software Carpentry: Unix, Git, and Python for Novices

Workshop dates: January 30-31

Instructors: Amanda Stahlke, Breanna Sipley, Salvador (Chava) Castaneda Barba, and Clint Elg

Description: Software Carpentry  aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation in Unix, GitHub, and Python. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. The course is aimed at graduate students and other researchers. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.  Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. More details can be found at https://astahlke.github.io/2020-01-30-uidaho/.

STUDENT Registration Link

NON-STUDENT Registration Link: Software Carpentry: Unix, Git, and Python for Novices


Introduction to R for Reproducible Science

Workshop dates: February 27-28

Instructors: Lihong  Zhao and Amanda Culley

Description: This introductory course will showcase reproducible research through simple analysis examples. The goal is to teach novice programmers to write modular code and best practices for using R for data analysis. This 2-day hands-on short course will give participants a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching basic programming in R, and will not teach statistical analysis. No prior knowledge of R or RStudio is needed. More details can be found at https://slihongzhao.github.io/2020-02-27-uidaho/.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). Please ensure you have the latest version of R and RStudio installed on your machine.

STUDENT Registration Link

NON-STUDENT Registration Link: Introduction to R for Reproducible Science


Data Carpentry – Geospatial Analysis

Workshop dates: March 26-27

Instructors: Erich Seamon and Travis Seaborn

Description: This hands-on workshop will focus on managing and understanding spatial data formats, understanding coordinate reference systems, and working with raster and vector data in R for analysis and visualization. An introductory knowledge to R is helpful, but not required. Participants will be encouraged to help one another and to apply what they have learned to their own research problems, and will be aimed towards graduate students and other researchers.

Attendees must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. More details can be found at https://erichseamon.github.io/2020-03-26-uidaho-geospatial

STUDENT Registration Link

NON-STUDENT Registration Link: Data Carpentry – Geospatial Analysis


College of Science Faculty Publish Ground-Breaking Study on Darwinian Genetic Evolution

College of Science faculty Jessica Lee, Siavash Riazi, Shahla Nemati, Jannell Bazurto, Andreas Vasdekis, Benjamin Ridenhour, Christopher Remien and Christopher Marx had a paper published in PLOS Genetics. In their research, they uncovered that genetically identical cells can be phenomenally different in their ability to survive stress, and thus selection acts upon the distributions of phenotypes without leading to genetic changes. They also found that stress tolerance changes with the environment, and there is even a form of memory that takes place as a result. These phenomena are being discovered in many realms, including cancer, where there are often “phenotypic mutations” which may seem like genetic change, but are not. This study opens the door to studying the entanglement of Darwinian genetic evolution with Lamarckian phenotypic evolution. Read the full article.

Answering Questions with Keystrokes

Answering Questions with Keystrokes

A special thanks to U of I science writer Leigh Cooper in Communications and Marketing for helping us celebrate IMCI molecular modeler, Dr. Jagdish Patel! View the original article in the College of Science’s feature section. Some of Jagdish’s work was recently published in Science Magazine. He is an accomplished researcher and we’re proud to have him on our team.


IMCI’s Jagdish Patel Uses Computer Models to Probe Microscopic Worlds

photo of Jagdish Patel
Jagdish Patel, Research Assistant Professor

The word “model” evokes many images such as a woman strutting down a Fashion Week runway or a model home. For scientists, a model represents a complex system such as the ocean’s currents or the economy. Scientists construct computer models to analyze, explain and simulate situations too multifaceted to study in the real world.

When molecular modeler Jagdish Patel sits down at his keyboard, he doesn’t model global markets or fancy homes. Instead, the University of Idaho research assistant professor focuses on how microscopic biomolecules interact.

“It’s all about creating a computer-generated world that mimics reality,” Patel said. “A good model helps answer real-world questions.”

A Microscopic World

Patel and U of I developmental biologist and vision scientist Deb Stenkamp wanted to understand the relationship between proteins and color vision. As members of the Institute for Modeling Collaboration and Innovation (IMCI) — U of I’s multidisciplinary, collaborative research program that houses biomedical research modeling experts — they began studying opsin proteins, which are light-sensitive proteins in the eye. IMCI’s Modeling Access Grant funded their work.

Jagdish Patel stands in front of a number of the deep-sea fish they used in their opsin experiment.

“If we succeeded, we could ask questions about the evolution of sight and afflictions of the eye that would be too expensive or time consuming to test using lab-based experiments,” said Patel, who is in the Department of Biological Sciences.

To achieve this goal, Patel first generated a 3D model of the opsin protein from its amino acids, the building blocks of a protein. Although complex at the molecular scale, the basic shape of an opsin is simple — it’s a cage. Patel then brought the cellular environment to life by adding the movements resulting from being in eye fluid.

During his research, Patel was specifically interested in asking questions about a chemical called retinal, which sits within the opsin. The retinal is basically a bird in an opsin cage, Patel said.

Depending on little differences in the sequence of amino acids that form the opsin cage, the shape of the retinal may change. Changes to retinal configuration can result in an animal seeing a greater range of colors. For instance, a mutation within a species that sees only green light may tweak the conformation of retinal enough that the species can see green and blue light.

Previous research documented the relationship between specific retinal conformations and opsin configurations and the color an animal sees. Knowing this relationship, Patel can, within his model, alter an opsin amino acid sequence, identify resulting changes to retinal conformation and make predictions about the colors the animal can see.

The task Patel and the rest of the team attempted was very difficult, and none of them were sure it would succeed. But it did, said Holly Wichman, director of IMCI, and it has led to multiple publications and two international collaborations.

“This demonstrates the power of interdisciplinary teams and reinforces the IMCI motto — modeling improves research at every stage,” said Wichman.

Bring in the Modeler

Patel is now tackling a wide variety of questions related to eyesight. He helped an international group of researchers investigate vision in deep-sea fish using his modeling approach. The deep-sea fish had opsins in light-sensitive cells called rods, which are usually used for night vision, not color vision. Using Patel’s approach, the study concluded some deep-sea fish species may have highly sensitive, rod-based color vision, likely green and blue.

Patel is also working with Chinese and British collaborators to study bats that have lost the ability to see ultraviolet light. In addition, Patel is a project director on an IMCI pilot grant to develop a tool that predicts how small changes in the amino acids that make up opsin affect the colors the opsin detects. Patel hopes his findings will be a steppingstone toward engineering opsins suitable for optogenetics — using light and genetic engineering to control brain cells — or developing targeted therapeutic strategies for eye diseases.

“Molecular models can solve such different problems,” Patel said. “On one hand, I’m currently using models to design anti-depressant and anti-cancer drugs. But I’m also helping a team from U of I’s Virtual Technology and Design build an educational tool for interacting with proteins in virtual reality.”

In addition, modeling has led Patel into pharmaceutical research involving the devastating Ebola virus. He screened thousands of computer-simulated molecules against a 3D model of Ebola virus protein to identify the molecules that might block Ebola virus’ ability to attach to humans. Currently, Patel is looking into patenting the most promising molecules.

“With a molecular model, you see things that you can’t see even with a microscope,” Patel said. “It’s a privilege to be the first one to see these events taking place at a molecular level.”

Article by Leigh Cooper, University Communications and Marketing

Photos by Melissa Hartley, University Communications and Marketing

Published November 2019.

This project was funded under National Science Foundation award 1736253. The total project funding is $6 million, of which 100% is the federal share. This project was funded under the National Institutes of Health National Institute of General Medical Sciences award P20GM104420. The total project funding is $10,572,579, of which 100% is the federal share.

Our Look

Our Look

A new look, or graphic treatment, is part of our transition from a center (CMCI) to an institute (IMCI).

In October, Creative Services attended a Brown Bag Lunch to talk about the U of I brand. They also collected input and ideas from participants for an IMCI graphic.

All of it is so that we can communicate effectively and consistently. View the pdf version of Creative Services’ presentation.

University Communications & Marketing also offer the following resources for your use and reference:

Visual Style Guide
How to represent U of I

Brand Toolkit
Contains templates, downloadable logos, font links,
photo assets, email signature, etc.

Sample Work
Samples of marketing pieces created
within the U of I brand guidelines

Stay tuned for more information!