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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.

U of I-Led Study Finds Experimental Fences Deter Elephant Crop Raiding, Provide Income

U of I-Led Study Finds Experimental Fences Deter Elephant Crop Raiding, Provide Income

This article was written by Leigh Cooper in University of Idaho Communications and Marketing. View the original article here. While IMCI was not involved in the funding of this research project, we are are thrilled to count Dr. Ryan Long as one of our participating faculty.


MOSCOW, Idaho – October 17, 2019 – A University of Idaho-led team of researchers found that experimental fences reduced the number of times elephants left Mozambique’s Gorongosa National Park to raid nearby crops by 80-95%; beehive fences appeared to be the most effective at deterring crop raiding while also providing a revenue source for neighboring villages through the production of honey.

Two male elephants approach a beehive fence. Image by University of Idaho.

The team’s evaluation of various fencing strategies for discouraging crop raiding by elephants outside Gorongosa was published today in Conservation Letters.

Crop raiding by wildlife results in billions of dollars in economic losses globally and threatens wildlife conservation efforts by creating negative human attitudes toward wildlife. Human and wildlife conflict can be exacerbated near protected areas like Gorongosa National Park, where the elephant population has risen to roughly 600 after falling by more than 90% during a civil war in the 1970s-90s.

“The better the elephant population does, the more animals leave the park and raid crops. That becomes a legitimate issue for the people living near the park as they are mostly subsistence farmers,” said Ryan Long, a U of I assistant professor and a lead researcher on the paper. “Negative interactions can lead to elephants being killed by people, or people being killed by elephants.”

Long, master’s student Paola Branco and colleagues tested the effectiveness of different fences at discouraging elephants from leaving the park. The study area incorporated four communities along 11.6 miles of the Pungue River, which marks the park’s southern border. The team fenced 13 of the 18 elephant river crossings in the study area. They used multiple fence types including beehive fences — free-swinging hives connected with twine — and chili fences — woven fabric soaked with chili-infused vegetable oil.

The researchers tracked elephant movements through GPS collars placed on 12 male elephants, camera-trap data and local reporting; they compared the number of elephant crossings in fall 2016 before fences were erected to the number of elephant crossings in fall 2017 when fences were in place. The number of crossings in the study area fell from 67 to 32, and the mean number of crossings at fenced locations decreased from 4.4 to 1.0.

The beehive fences appeared to be the most effective deterrent — a 95% reduction in crossings was observed — although the small sample size didn’t allow for statistical differentiation among fence types, Long said. The study indicates various fences can reduce crop raiding, and working with local communities to modify animal behavior and human attitudes simultaneously can mitigate human and wildlife conflict.

“To be effective, mitigation must be affordable and maintained locally. There must be an incentive to maintain them, and they need to improve the perception of wildlife by locals,” Long said. “We picked these fences because, first, it’s cost-prohibitive to create a physical barrier to stop the largest land mammal on Earth, especially across a large area. Secondly, there’s intrinsic motivation for the communities to maintain these fences over the long term, both for the purpose of deterring elephants and for the purpose of producing a marketable product, honey.”

The initial cost of fence construction was borne by the park and donors, while local communities were responsible for maintenance and harvest and sale of the honey. A beehive fence with 15 hives, like the ones used in the study, can generate from two to four times the current minimum annual wage in Mozambique. Based on the study’s results, the Conservation Department of Gorongosa is now deploying beehive fences at crossings all along the Pungue River.

This project was funded under National Science Foundation award 1656642. The total project funding is $700,000, of which 100% is the federal share.

Media Contacts

Ryan Long
Assistant Professor of Wildlife Sciences
Department of Fish and Wildlife Sciences
208-885-7225
ralong@uidaho.edu

Leigh Cooper
Science and Content Writer
University of Idaho Communications and Marketing
208-885-1048
leighc@uidaho.edu

About the University of Idaho

The University of Idaho, home of the Vandals, is Idaho’s land-grant, national research university. From its residential campus in Moscow, U of I serves the state of Idaho through educational centers in Boise, Coeur d’Alene and Idaho Falls, nine research and Extension centers, plus Extension offices in 42 counties. Home to nearly 12,000 students statewide, U of I is a leader in student-centered learning and excels at interdisciplinary research, service to businesses and communities, and in advancing diversity, citizenship and global outreach. U of I competes in the Big Sky Conference. Learn more at uidaho.edu

Which comes first, the chicken or the egg?

Which comes first, the chicken or the egg?

World-wide experiments have been conducted to understand the distinct relationships among various genes. However, it remains a challenge to identify the genomic causes and effects directly from the data, especially within a network. It’s the classic chicken and egg question: Which comes first, the chicken or the egg? In other words, how do you know which genes regulate which other genes?

Correlation between the expression of two genes is symmetrical. Therefore, scientists cannot infer which of the two genes is the regulator and which is the target. Similar levels of correlation can arise from different causal mechanisms. For example, between two genes with correlated expression levels, it is plausible that one gene regulates the other gene; it is also plausible that they do not regulate each other directly, but are regulated by a common genetic variant.

Audrey Fu, Assistant Professor in the Department of Statistical Science, and Postdoctoral Researcher Md. Bahadur Badsha, recently published a paper introducing a novel machine learning algorithm. “Our new method, namely the MRPC algorithm, can tease apart which correlation may suggest causality and which correlation is just indirect association through many other genes,” said Fu.

Figure 2. The MRPC algorithm. The MRPC algorithm consists of two steps. In Step I, it starts with a fully connected graph shown in (1), and learns a graph skeleton shown in (2), whose edges are present in the final graph but are undirected. In Step II, it orients the edges in the skeleton in the following order: edges involving at least one genetic variant (3), edges in a v-structure (if v-structures exist) (4), and remaining edges, for which MRPC iteratively forms a triplet and checks which of the five basic models under the PMR is consistent with the triplet (5). If none of the basic models matches the triplet, the edge is left unoriented (shown as bidirected). (A) An example illustrating the algorithm. (B)The pseudocode of the algorithm. 

Reproducibility Does Not Equal Truth

Reproducibility Does Not Equal Truth

The CMCI Reproducibility in Sciences working group, or SciRep for short, has been meeting since the fall of 2015. Today, their most recent publication, “Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity,” was published in PLOS ONE. Congratulations!

Fig 2. A transition of our process of scientific discovery for an epistemically diverse population with replicator. A scientist (Bo) is chosen uniformly randomly from the population (1). Given the global model, the set of proposal models and their probabilities (given in percentage points inside models) are determined. In this population with no replicator, Bo proposes only models formed by adding an interaction (2). The proposed model selected (3) and the data generated from the true model (4) are used with the model comparison statistic (SC or AIC) to update the global model (5).

The American Council on Science and Health also picked up the story with their article, “Reconsidering The ‘Replication Crisis’ In Science.”

The following article was written by Leigh Cooper, U of I Science and Content Writer.


U of I Study Finds Scientific Reproducibility Does Not Equate to Scientific Truth

MOSCOW, Idaho — May 15, 2019 — Reproducible scientific results are not always true and true scientific results are not always reproducible, according to a mathematical model produced by University of Idaho researchers. Their study, which simulates the search for that scientific truth, was published today, May 15, in the journal PLOS ONE.

Independent confirmation of scientific results — known as reproducibility — lends credibility to a researcher’s conclusion. But researchers have found the results of many well-known science experiments cannot be reproduced, an issue referred to as a “replication crisis.”


“Over the last decade, people have focused on trying to find remedies for the ‘replication crisis,’” said Berna Devezer, lead author of the study and U of I associate professor of marketing in the College of Business and Economics . “But proposals for remedies are being accepted and implemented too fast without solid justifications to support them. We need a better theoretical understanding of how science operates before we can provide reliable remedies for the right problems. Our model is a framework for studying science.”

Devezer and her colleagues investigated the relationship between reproducibility and the discovery of scientific truths by building a mathematical model that represents a scientific community working toward finding a scientific truth. In each simulation, the scientists are asked to identify the shape of a specific polygon.

The modeled scientific community included multiple scientist types, each with a different research strategy, such as performing highly innovative experiments or simple replication experiments. Devezer and her colleagues studied whether factors like the makeup of the community, the complexity of the polygon and the rate of reproducibility influenced how fast the community settled on the true polygon shape as the scientific consensus and the persistence of the true polygon shape as the scientific consensus.

Within the model, the rate of reproducibility did not always correlate with the probability of identifying the truth, how fast the community identified the truth and whether the community stuck with the truth once they identified it. These findings indicate reproducible results are not synonymous with finding the truth, Devezer said.

Compared to other research strategies, highly innovative research tactics resulted in a quicker discovery of the truth. According to the study, a diversity of research strategies protected against ineffective research approaches and optimized desirable aspects of the scientific process.

Variables including the makeup of the community and complexity of the true polygon influenced the speed scientists discovered the truth and persistence of that truth, suggesting the validity of scientific results should not be automatically blamed on questionable research practices or problematic incentives, Devezer said. Both have been pointed to as drivers of the “replication crisis.”


“We found that, within the model, some research strategies that lead to reproducible results could actually slow down the scientific process, meaning reproducibility may not always be the best — or at least the only — indicator of good science,” said Erkan Buzbas , U of I assistant professor in the College of Science , Department of Statistical Science and a co-author on the paper. “Insisting on reproducibility as the only criterion might have undesirable consequences for scientific progress.”

Ebola Research Publication Featured

Congratulations to Jagdish Patel and Marty Ytreberg! Their article, “Expanding the watch list for potential Ebola virus antibody escape mutations” was recently selected to be featured on the

PLOS Ebola Channel.

The PLOS Ebola Channel was launched in response to the ongoing Ebola outbreak in the Democratic Republic of Congo. They work with authors and editorial boards to provide rapid review and facilitate the responsible dissemination of preprints. These responses are needed during serious and rapidly developing threats to public health. The PLOS Ebola Channel will make it easy for researchers to keep up with developments and important research related to the outbreak.