bioinformatics

Killing Cancer with Code

September 4, 2020 By Lauren Hines in Research Tags: aptamers, bioinformatics, cancer

Microscopy Images and Maps of Receptors in a Cancer Cell — These maps show the receptors’ locations, density and count in a cancer cell. | photo contributed by Alexander Jurkevich, Donald Burke-Agüero, David Porciani and Skyler Kramer.

By Lauren Hines | Bond LSC

With two laptops in front of him and a supercomputer on the edge of campus, graduate student Skyler Kramer runs through code daily in the Dong Xu lab with a purpose far beyond deciphering lines of data. He helps his colleagues defeat cancer.

Working in Bond LSC with senior post doctorate David Porciani from the Donald Burke lab, Kramer and the Dong Xu lab are part of an effort to target cancer tissue and develop more precise delivery of treatment.

In addition, they’re trying to learn more about the biology that drives cancer growth and what makes cancer tissue resistant to treatment after a certain point in time.

“[Kramer] has been a tremendous asset for the project,” Porciani said. “His contribution is so critical at many levels.”

Porciani set out four years ago to find a way to easily differentiate between cancer and healthy tissue. By developing small pieces of RNA and DNA called aptamers that can bind to receptors on cancer cells, he slowly tried to determine the pieces that would only interact with cancer — not bothering the healthy cells — that could deliver a cancer-killing drug. But the process meant Porciani would amass mounds of data.

“There is a lot of statistics in there, which is very important,” Porciani said. “So, that brings in the collaboration with Skyler.”

About a year ago, Porciani was presenting his work on aptamers at a talk in Bond LSC. Xu later inquired if Porciani was open to any collaboration, which led to discussion on what the two labs could do together.

“It was just really really fascinating,” Kramer said. “So, I was really interested in it.”

Now, the two are working together to turn microscopy images into something more meaningful.

Through super resolution microscopy images of the receptors on the cancer cells, Porciani took a short video showing the thousands of receptors shaking.

“Most of the receptors like to shake hands with each other, and when that happens it is critical for the growth of the cells,” Porciani said. “So, the handshakes are sort of a signal that says, ‘Okay, let’s move this house to the next stage. Yes, let’s make the cell grow even more.’”

Porciani could analyze only a small part of these shakes with his naked eye but using a bioinformatics approach —using software and statistics to understand biological data — Kramer can take that data from the thousands of receptors and turn it into digestible and meaningful information.

“[I’m] trying to take the massive amounts of data that we’re able to generate and get some sort of useful information out of it,” Kramer said. “So, a lot of times it’s useful not only to get some sort of numeric output but some sort of visualization also.”

This means turning an image of a cancer cell into a receptor density map or a receptor count map. By doing so, researchers can investigate why receptors clump into one area, what that means and why cancer cells become resistant to treatment over time.

“It’s our job to understand why there is this difference,” Porciani said. “This type of information can generate new hypotheses that we need to test.”

With the help of bioinformatics, Porciani and other researchers can find the answers to their questions.

“I think [bioinformatics] is hugely impactful,” Kramer said. “A lot of times, the life sciences will give you the actual experiments and a rough idea of what happened in the experiment, but I think that when you apply the bioinformatics you get more to why specific things are happening.”

The collaboration brings more than just new results, but also can help expand science.

“I think I’m learning a lot from him,” Porciani said. “I think, hopefully, he is learning a lot from me as well.”

To learn more about Porciani and Burke lab’s findings regarding aptamers, the research article can be found here.

#IAmScience Landon Swartz

May 29, 2020 By Lauren Hines in #IAmScience Tags: bioinformatics, computer science

By Lauren Hines | Bond LSC

Landon Swartz, undergraduate student researcher, is motivated by a simple desire — to help others through the power of computer engineering.

Coming from Springfield, Missouri, Swartz decided to go to Mizzou in 2017.

“I chose engineering,” Swartz said. “It fits my idea of solving problems, but also lets me be able to see a benefit to people.”

Swartz got involved in research through the honors college after he talked to David Mendoza, associate professor in plant sciences and Bond LSC investigator. Mendoza was looking for people to help program and build his data collection machines.

“Robotics is right up my alley,” Swartz said.

In the Mendoza lab, Swartz was modeling the robot and programming it to move, take pictures and run diagnostics.

This experience eventually led Swartz to win the summer 2020 Cherng fellowship from the MU honors college. The nine-week research program provides networking and presentation events along with a $1,000 project expense account.

“It feels really great,” Swartz said. “It was really nice to be able to win that because you do have to plan a full project, like, the beginning, middle and end of everything. So, it’s nice to be able to not only plan that out, but to actually get to do it and get the funding and support to do it.”

The fellowship will help Swartz create his own idea for a robot. After seeing the potential of the robot that images root growth in Mendoza’s lab, Swartz wanted to expand it further by adding an automated hydroponic system.

The system will help researchers easily control variables that will affect the plant and watch how physical traits are affected.

“The reason I came up with the idea for hydroponics is because after watching my lab mates try to do hydroponics, it’s a very labor-intensive procedure,” Swartz said. “It’s a very error prone procedure because you have to do everything manually.”

In addition to saving time for researchers, the robot will also potentially help eliminate human bias in research and increase efficiency.

Since Swartz’ project straddles plant biology and engineering, funding can be hard to find.

“If you can’t find that enthusiasm from grants or any other place, you kind of have to figure it out along the way,” Swartz said. “So, this fellowship will help us a lot with kind of establishing more examples of how you can use automated phenotyping.”

When Swartz isn’t working in the lab or going to his computer engineering classes, he can be found practicing bass guitar, playing the trumpet or running the soundboard for a college ministry on campus.

“Whenever I get confronted with a problem, I usually go and practice for a while just because I feel like it opens up another side of my brain,” Swartz said.

Swartz has been playing the trumpet since middle school and the bass guitar since freshman year of college. Swartz sees the importance of his research even in music.

“Seeing where engineering intersects with plant biology and healthcare and going back to music, like audio equipment, things like that, there’s engineering and everything,” Swartz said.

Swartz sees the potential and power of computer engineering and how it can help people and researchers alike. He plans to be in the lab this summer to try and make that potential a reality.

“Knowing you’re going to be a piece in a puzzle to something greater…. that’s what keeps me going,” Swartz said.

The Little Robot That Can

May 13, 2020 By Lauren Hines in Research Tags: bioinformatics, computer science

Root Imaging System — The imaging system helps collect data on the growth of plants. | photo contributed by Samuel McInturf.

By Lauren Hines | Bond LSC

In a corner of the David Mendoza lab, a small machine runs back and forth across a track, taking pictures continuously of plants grown in clear square plates. This machine not only saves time during data collection but also helps the lab track the growth of plants in real time.

After almost five years of development, the Mendoza lab has reached the final stretch in their robotic endeavors. Now, they’re putting the finishing touches on the machine and getting a scientific article together to be submitted in a peer-reviewed journal.

“A few years back, we realized that our phenotyping methods were insufficient to capture subtle changes, things that aren’t just screamingly obvious, and although small, they’re very important,” said Samuel McInturf, a molecular biologist who is part of David Mendoza’s lab. “So, I set out and learned a whole bunch of stuff about robotics.

The project idea came into being in 2015 and transformed itself into a bioengineering senior capstone class where Mendoza, McInturf and many students from bioengineering, computer science and computer engineering worked on creating different prototypes of this idea.

“We are rapidly moving into a phase of a modular revolution, where our older methods, such as phenotyping by eye, aren’t really going to be sufficient,” McInturf said. “So, these machines represent a transition into mechanization or automation of our current methodologies.”

In addition to making the lab more efficient, the machine makes experiments more reliable.

“[The machine] really decreases the bias, decreases human intervention and increases the amount and quality of data that we are gathering,” said David Mendoza, associate professor in plant sciences and Bond LSC investigator.

Another benefit the robot offers to other labs is that it allows undergraduates to do more.

“[Undergrads] did a lot of repetitive tasks, but we are evolving as a society, so now you can teach them to do a lot of different assays and a lot of more complicated, sophisticated things using robotics,” said Ron Mittler, professor of plant sciences and Bond LSC investigator. “So, I look into this as a big advantage, actually.”

Now that the robot has proved effective, the next step is to share it with others. Last summer, McInturf and others flew to Africa to build a version of the robot for the University of the Western Cape in South Africa but wants labs at MU to use their work.

“The idea was to make the machines not just for us but for labs across the world,” said Landon Swartz, an undergraduate student researcher who is part of the project. “I’m hoping to see us be able to get machines out to other labs and just see how it affects their research and how much good can come from it.”

Soon to be one of their first users, Mittler needs the robot to help screen through the 1,000-3,000 plates his lab ends up with that need to be imaged, measured and processed to determine root growth and other parameters

“If you can optimize processes like that, then you can screen a lot of mutants,” Mittler said. “You can do a lot of different things that will take a lot of time and energy, and then you will not have to always spend power or time on data collection…That’s something that a lot of labs would have liked to have, including mine.”

Even though there’s a paper underway and labs are eager to get their own robot, the Mendoza lab isn’t yet finished with the project.

“Feels good to reach a benchmark,” McInturf said. “But there’s still so much more that we can expand upon.”

As of now, this particular machine is used to track the growth of roots and shoots of plants. However, the robot has potential to do even more.

“Now that we’ve developed all of this expertise, it’s relatively simple to add a heat sensitive camera, so we can see how active a plant’s metabolism is,” McInturf said. “Perhaps we could find a way to measure photosynthesis on the fly. Those types of expansions would be much more powerful.”

But for now, the Mendoza lab is busy writing manuscripts, doing proof of concept experiments and updating the software and user interface for the paper, which is scheduled to be submitted for review within the next few weeks.

Dong Xu receives national honor

April 16, 2020 By Roger Meissen in Research Tags: bioinformatics

*Dong Xu, Bond LSC principal investigator and Shumaker Endowed Professor in the University of Missouri’s College of Engineering. | photo by Roger Meissen, Bond LSC*

A Bond Life Sciences Center researcher has been inducted into an elite organization comprised of two percent of all medical and biological engineers.

The American Institution for Medical and Biological Engineering (AIMBE) this week announced the induction of Dong Xu, a Bond LSC principal investigator and Shumaker Endowed Professor in the University of Missouri’s College of Engineering.

“Election to the AIMBE College of Fellows is among the highest professional distinctions accorded to a medical and biological engineer,” said Kamrul Islam, chair of the college’s Electrical Engineering and Computer Science department.

Xu was selected for his “distinguished contributions to bioinformatics and computational biology, and extensive services to University of Missouri and his research community.”

In addition to his endowed faculty position, Xu serves as director of the Information Technology program, whose core facility is housed in Bond LSC.

Membership to AIMBE’s College of Fellows recognizes those who have made outstanding contributions to engineering and medicine research, practice or education, and to those pioneering new and developing fields.

Because of health concerns, AIMBE’s annual meeting and induction ceremony scheduled for this spring was canceled. Under special procedures, the induction was held remotely.

Another Piece of the Pi: Tech gives research automation edge

February 12, 2020 By Mariah Cox in Research Tags: bioinformatics, computer science

This Raspberry Pi device developed by former MU undergrad Brandin Grindstaff allowed members of the Chris Pires lab to remotely monitor their plants. | photo by Roger Meissen, Bond LSC

By Mariah Cox | Bond LSC

What does an iconic American dessert have in common with a credit-card-sized single-board computer? Well, only its name.

Small but mighty, the Raspberry Pi can be programmed for use in multiple settings and has been increasingly used for tasks in research labs.

But it took a scientific conference in Europe for one Bond LSC lab to tap into its usefulness. Makenzie Mabry, a doctoral candidate in the Chris Pires lab, found herself with the dilemma that she couldn’t monitor her research plants back home in the lab across an ocean. This predicament sparked an idea in biology undergraduate Brandin Grindstaff, who found the solution and the hands-on research opportunities he was searching for.

“Ever since I can remember I’ve been fascinated by biology and technology. Computer science is an important component of biological research,” Grindstaff said. “Programming, specifically, is a really powerful tool for a researcher and it can be indispensable for collecting data or solving problems that might be impossible without it.”

While computer programming was a foreign skill for Grindstaff, the unfamiliarity was a motivator. Grindstaff proposed an idea for a small plant growth chamber monitor to Pires and Mabry his final semester of undergrad and began development the following summer. The Growth Monitor pi (GMpi) tracks the functionality of designated room parameters, meaning if a light goes out or someone left the door open, it sends a Slack message to all members of the lab.

Brandin Grindstaff poses with some plants in a growing room. | Photo courtesy of Grindstaff

Without any prior experience working on Raspberry Pi’s, electronics, or with the Python program language, he spent a large chunk of time teaching himself.

“Every day was a new and interesting challenge interfacing the sensors and camera with the Raspberry Pi. I spent hours sifting through tutorials and Python and Linux documentation,” Grindstaff said. “After a few weeks, we got the first iteration set up for testing the growth chamber, but it would crash after only a few hours of automation because something was causing the code to break.”

This hands-on participation in a lab was hugely important to Grindstaff’s college experience. As a first-generation college student, he often found himself struggling to navigate higher education. Before his work on GMpi, Grindstaff spent time on other projects but had a hard time finding his fit. At that point, Grindstaff was about to leave the lab, but he saw the opportunity for the device and made his case.

“Chris and Makenzie took a chance on me because I was passionate about research, not because I had the best grades. The GMpi project would have been a tough sell to most mentors, but they gave me a chance,” Grindstaff said. “Education and internship opportunities need to be more accessible to everyone, especially first-generation college students.”

For Mabry, his mentor, the project was important because it was entirely led by one of her undergrads who eventually was first author on a journal publication.

“It’s really rewarding when I get my own stuff published, but to have someone that you’ve mentored be so successful, it’s even more meaningful,” Mabry said. “The value of undergraduate research is making sure people have those opportunities.”

Devices using the Raspberry Pi are becoming more prevalent in research settings to streamline lab processes. The core computer costs roughly $40 and GMpi’s attachments added up to $200. Other systems that are used to monitor growing environments typically cost thousands of dollars.

Grindstaff’s work in the Pires lab earned him attention from businesses who’ve asked him to develop similar devices. One year out of college, Grindstaff is still on the hunt for a job but in the meantime, he’s working on an expanded monitoring system for use in a commercial cultivation facility to track more environmental parameters and automate a large part of the cultivation process.

“Devices like the Raspberry Pi, open-source communities, and tutorial creators make this sort of technology accessible to everyone. You don’t really have to know anything about computer science to get started,” Grindstaff. “More than anything, I hope this project makes researcher’s lives a little easier, or even inspires somebody else to create something awesome.”

Grindstaff graduated from MU with a degree in biological sciences in 2018. His research was published in the Journal “Botanical Society of America” in Aug. 2019.

#IAmScience Trupti Joshi

November 30, 2018 By Erica Overfelt in #IAmScience Tags: bioinformatics

By Erica Overfelt | Bond LSC

Juggling research, teaching, collaborative meetings, grant writing, and training postdocs and students is no problem for Trupti Joshi.

That array of responsibilities is just part of the job for a Bond LSC researcher focused on bioinformatics, an area that connects so many types of science by collecting and analyzing genetic data.

“Bioinformatics is a very interdisciplinary science that marries the wet and the dry labs,” Joshi said. “It applies software tools and computational techniques from computer science, engineering, mathematics and statistics towards efficient ways to analyze, integrate and mine large-scale genomics and multiomics datasets from biological, plant and biomedical sciences. This research aids in the use of genomics in all areas of life and science from food and crop production decisions based on climates to healthy lifestyle and drug development for treatments.”

Dealing with genetic data might seem dry, but Joshi said the tools it uses answers questions that touch many areas of our world.

“Every aspect in everyone’s life touches genomics,” Joshi said. “What we do in genomic studies is important because it can be really important for the common man. Where did the roses get their fragrance or their beautiful petals? How did this emerge? Or at the same time why does the fruit taste bitter or sour? It comes down to that genomic blueprint.”

While you can often catch Joshi doing research at one of her labs in Bond LSC and School of Medicine, her area is applicable to almost every corner of campus. That’s reflected in her many positions and titles across MU. She’s director of translational bioinformatics and assistant professor in the Department of Health Management and Informatics, has appointments as core faculty with the Informatics Institute, the Interdisciplinary Plant Group, the Department of Computer Science and a primary investigator at Bond LSC.

Though Joshi trained as a clinical doctor prior to her doctoral degree, she believes she was destined to become involved with bioinformatics. While she loves to draw and thought about architecture, her family’s trajectory always influenced her toward science. With her father being an engineer, her mother a mathematician, one sister a doctor and the other a computer science engineer, bioinformatics field gave a chance to marry all of these fields into one and be able to do a bit of everything.

“My sisters and my parents motivated me, instilled the liking for science and overall higher education have been the pillar of what our parents have stressed in our family,” Joshi said. “It comes to your thinking and carving your career path. My sisters’ careers provided me an opportunity to see both clinical and engineering fields really closely, and that inspired me to pick the unconventional path because I could see a bit of both in me.”

Joshi hopes she influences others in their career paths.

“What I feel is important for my graduate students and post docs is encouraging them to define their skills,” Joshi said. “Some may be teaching or being a faculty or setting up their own industry. I think that really ends up being the force behind you and makes your life and career interesting.”

And the constant interaction with collaborator has kept her eager to get to the lab each morning and making discoveries for 18 years.

“What I feel is important in a career is that you are really interested and passionate about your work,” Joshi said. “It is the driving force to starting your day. If the questions you are working on are uninteresting it affects your life. I like to be ambitious and set the bar high, so one can break one’s own records.”

#IAmScience Juexin Wang

October 5, 2018 By Erica Overfelt in #IAmScience Tags: bioinformatics

By Erica Overfelt | Bond LSC

Boring may not be the first word that comes to mind when you think of someone’s research story.

But for Juexin Wang, it was a dull job that steered him toward research.

“My undergrad was in Beijing, I was studying computer science,” Wang said. “After I finished my undergrad I went to work in the industry for two years as a software engineer, and I realized that work was so boring to me and I wanted to discover something new.”

Wang went back to school for his masters and Ph.D. in Northeast China. During his Ph.D., Wang had an opportunity to collaborate with Dong Xu in Bond LSC, and he took the chance to come to the states.

“The most advanced technologies were here,” Wang said. “I felt really comfortable when I came here, we could adjust the focus on the research and the platform Mizzou provided was powerful. We have great collaborators, and I think if you have questions people are happy to help you.”

Eight years later you can find Wang going back and forth between the School of Medicine and Bond LSC. His research works with both Dong Xu and Trupti Joshi to combine biology and data sets, a field known as bioinformatics.

“I found possible connections between computer science and biology,” Wang said. “Data that comes from biology reflects biological mechanism on different levels. With computers, software, the algorithms, we can find something new no one has ever seen in wet lab, which may help people understand diseases in human beings and complex traits in other organisms such as plants.”

Wang’s research involves creating new tools and algorithms for the data sets.

“My work has many tasks,” Wang said. “I do algorithms development, and if we have too much data — you can call it ‘big data’ — this causes us to develop new tools that can help understand and tie into the data. My work is trying to develop different tools to help people deal with this same problem in data on their own.”

Too much data, too little time, is why people like Wang are advancing in this science.

“For me, I never found anything really new in my software engineering work, but in research I always touch something new,” Wang said. “New mechanism, new data, new tools. I think that it is fascinating, you always put your passion over yourself. You’re always pushed and this isn’t like anything else.”

#IAmScience Duolin Wang

February 23, 2018 By Allison Scott in #IAmScience Tags: bioinformatics

By Allison Scott | Bond Life Sciences Center

“#IAmScience because I want to explore the beauty of biological sequences through computational methods.”

Bioinformatics is a melting pot in the world of science. As a study of analyzing complex data, it’s not a field for everyone, but its applications are vast.

Duolin Wang, a researcher in the Dong Xu Lab at Bond LSC, isn’t intimidated by the complexities her field presents. She came to America from China to conduct research for Xu’s lab while she simultaneously works on her thesis to earn her Ph.D. from Jilin University in China.

“The reason I came to American is because the education is great,” Wang said. “It provides me a very good opportunity to study and do research.”

Wang and her lab practice deep learning, which is a state-of-the-art approach to machine learning.

“There has been a growing interest in applying deep learning methods to understanding the function of biological sequences directly from sequence,” Wang said. “It allows computational models composed of multiple processing layers to learn representations of data with multiple levels of abstraction.”

Essentially, deep learning is a way to better understand the complex data that the bioinformatics field covers. For instance, it turns terabytes of information on a sequence to help researchers predict how best to improve its effectiveness.

She didn’t just stumble into her research position, though. Her supervisor at her university in China had collaborated with Xu in the past. When Xu traveled overseas, Wang was able to meet him in person.

“I showed my interest in his research, and I asked him if I could come to the United States to continue my research,” Wang said.

The rest is history. In the three years she’s been at Mizzou, Wang has been able to work on a number of projects in her field. That’s largely thanks to Xu’s flexibility with the topics she focuses on.

“I have freedom to choose what I want to study,” Wang said. “As a scientist, I can explore what I’m really interested in. Professor Xu didn’t make any barriers to my research field; I can show him my interests and he can see whether it’s a good topic and if I can explore it.”

Wang has even written a few papers, including one for Monsanto thanks to the help of Juexin Wang who also works in the Xu lab. That experience has helped her to prepare for a future in research writing proposals.

It’s not all about the work, though.

“The most valuable thing I got from this lab is the people,” Wang said. “They’re excellent scientists, and I’ve learned a lot from them.”

Wang is on track to finish her Ph.D. this summer, but she’d like to continue what she’s been doing at Bond LSC.

“I might do a postdoc here after I earn my degree,” Wang said. “I want to continue my research here.”

Drowning in Data

August 18, 2017 By Roger Meissen in Research Tags: big data, bioinformatics, KBCommons, Soy KB, soybeans

New web-based framework helps scientists analyze and integrate data

By Emily Kummerfeld | Bond LSC

Large-scale data analysis on computers is not exactly what comes to mind when thinking about biological research.

But these days, the potential benefit of work done in the lab or the field depends on them. That’s because often research doesn’t focus on a single biological process, but must be viewed within the context of other processes.

Known as multi-omics, this particular field of study seeks to draw a clearer picture of dynamic biological interactions from gigantic amounts of data. But, how exactly can scientists suitably weave multiple streams of information together, especially considering technology limits and other biological variables?

Trupti Joshi and her team are seeking to find a solution to that problem.

Joshi, as part of the Interdisciplinary Plant Group faculty, works on translational bioinformatics to develop a web-based framework that can analyze large multi-omics data sets, appropriately entitled “Knowledge Base Commons” or KBCommons for short. She describes KBCommons as “a universal, comprehensive web resource for studying everything from genomics data including gene and protein expression, all the way to metabolites and phenotypes.”

Her work began about eight years ago with soybeans. Dubbed the Soybean Knowledge Base (SoyKB), her team had developed a lot of their own data analysis tools for soybean research, but they realized the same tools could help research of other organisms. From there sprouted the Knowledge Base Commons, intended for looking at plants, animals, crops or disease datasets without the need to “reinvent the wheel” each time.

Soybean plants used in research that utilizes Soy KB web-based network. | Emily Kummerfeld, Bond LSC

“Our main focus has been in enabling translational genomics research and applications from a biological user’s perspective, and so our development has been providing graphic visualization tools,” Joshi said.

Those tools provide an array of colorful graphics from basic bar graphs to assorted colored pie charts to help the researcher better analyze the data once data has been added to the KBCommons.

Colorful graphs and comparisons lets many researchers look past the lines of text and tables full of numbers that represent genes, plant traits or other experimental results, and making the interpretation of data much more easier and efficient.

One particular tool allows the researcher to look at the differential genes of four different comparisons or samples at the same time. Differential genes are the genes in a cell responding differently between different experimental conditions. For example, a blood cell and a skin cell both have the same DNA, however, some genes are not expressed in the blood cell that are expressed in the skin cell. With this KBCommons tool, a researcher can examine genes to see “what are the common ones, what are the unique ones to that, and at the same time look at the list of the genes and their functions directly on the website, without having to really go and pull these from different websites or be working with Excel sheets,” Joshi explained.

She envisions KBCommons as a tool to enable translational research as well. Users will be able to compare crops, such as legumes and maize for food security studies, or link research between veterinary medicine and human clinical studies for better therapies.

Intended for a wide range of users, Joshi is keenly aware of its potential users right here at MU.

One current user of the Soybean Knowledge Base (SoyKB) system is Gary Stacey, whose lab at Bond Life Sciences Center studies soybean genomics and to date has been the longest user of the SoyKB resource. Like many researchers, Stacey explained the need for a program like SoyKB that can process enormous amounts of data.

“The reason it’s called “Knowledge Base” is the idea that we’re putting information in, and what we hope to get out is knowledge. Because information is different than knowledge,” he said, “we don’t just want to collect stamps, we want to be able to actually make some sense out of it…By having a place to store the data, and then more importantly have a place to analyze it and integrate it, it allows us to ask better questions.”

This is essential, given that one soybean genome is 1.15 GB in size, and one thousand soybean genome sequences could generate 30 to 50 TB of raw sequencing data and tens of millions of genomic variations (SNPs).

But such numbers are modest compared to the program’s true capabilities.

“The KBCommons system is so powerful that it can allow you to run thousands of genomes at the same time using our XSEDE gateway allocations,” Joshi said. “This whole scalability is a unique feature of KBCommons, which a lot of databases do not provide, and we are happy we have been able to bring that to our MU Faculty collaborators on these projects, so that they can really utilize the remote high performance computing (HPC), cloud storage and new evolving techniques in the field.”

KB Commons is a new web-based network for biological data analysis and integration developed by students. | Emily Kummerfeld, Bond LSC

Mass data capability and colorful graphs aside, her favorite part is who exactly is designing the program.

“What I like most about KBCommons is that it serves as a training and development ground and is developed by students, undergraduate and graduate students from computer science and our MUII informatics program.”

KBCommons is still under development, but publication and access for all users is planned for the end of this year or early 2018. Users will not only be able to view public data sets, but add their own private data sets and establish collaborative groups to share data.

Dr. Trupti Joshi is an Assistant Professor and faculty in the Department of Health Management Informatics, the Director for Translational Bioinformatics with the School of Medicine, and Core Faculty of the MU Informatics Institute and Department of Computer Science and the Interdisciplinary Plant Group.

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