Emerging Trends from a Bioinformatics Frontier
Proceedings of the 2015 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference
Imagine trying to understand the most complex instruction manual ever written—one with billions of letters, no punctuation, and multiple layers of hidden meaning. This is essentially the challenge that biologists face when working with genetic data, and it's precisely why the field of bioinformatics has become so crucial. In March 2015, over 150 scientists gathered in Little Rock, Arkansas, for the 12th annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS). Their shared goal? To decode life's instruction manual and translate these insights into real-world applications that could revolutionize medicine and biology 1 .
Under the theme "Emerging Trends in Bioinformatics," researchers presented groundbreaking work that straddled the line between computer science and biology.
From reducing uncertainty in understanding how genes interact to predicting adverse drug reactions through computational models, the conference showcased how data analysis is transforming biological research 1 . As one keynote speaker emphasized, we're moving toward an era where we can "experience data through interactive visual explorations"—making complex biological information tangible and understandable 1 . This article delves into the exciting discoveries and methodologies presented at this conference, explaining how computational approaches are reshaping our understanding of life itself.
The research presented at the MCBIOS conference generally fell into three broad categories, each tackling a different aspect of biological complexity using computational power.
Think of a city's road network—streets connect, traffic flows in specific patterns, and disruptions in one area can cause ripple effects throughout the system. Similarly, inside every cell, genes and proteins interact in complex networks, and understanding these connections is vital for deciphering how organisms function.
If our DNA is a biological instruction manual, then genomics involves reading this manual, while transcriptomics determines which instructions are being actively used at any given time.
Among the many presentations, one study stood out for earning the conference's Best Paper Award: "Efficient experimental design for uncertainty reduction in gene regulatory networks" by Roozbeh Dehghannasiri, Byung-Jun Yoon, and Edward Dougherty 1 .
Gene regulatory networks (GRNs) represent how different genes in a cell interact—turning each other on and off in complex cascades of activity. However, our understanding of these networks typically contains significant uncertainty. With thousands of genes interacting in non-linear ways, completely mapping a GRN would require an impractical number of experiments. Researchers needed a way to determine which specific experiments would provide the most information to reduce this uncertainty most efficiently.
Created "mean objective cost of uncertainty" (MOCU) to measure how uncertainty limited accurate predictions 1 .
Ranked potential experiments by their potential to reduce uncertainty per experimental effort 1 .
Cyclical approach where each experiment informed the next selection 1 .
Tested method on both simulated GRNs and real biological networks 1 .
| Method Type | Computational Cost | Uncertainty Reduction | Practical Application |
|---|---|---|---|
| Theoretical Optimal | Very High | Maximum | Limited to small networks |
| MOCU-Based Method | Moderate | Near-Maximum | Suitable for large, complex networks |
| Random Experiment Selection | Low | Minimal | Inefficient for large-scale studies |
This work has profound implications for personalized medicine. As the conference proceedings noted, cancer precision medicine uses genetic information from a patient's tumor to determine a therapy plan targeted to the particular genetic abnormality 1 . Methods that can more efficiently determine these abnormalities and their interactions will accelerate the implementation of truly personalized treatment approaches.
Bioinformatics research relies on both physical laboratory tools and sophisticated computational resources.
A significant focus was on the emerging field of precision medicine, an innovative approach that considers individual differences in people's genes, environments, and lifestyles 1 .
The cost of Whole Exome Sequencing had fallen to approximately $1,000—comparable to the price of a CT scan—suggesting that NGS assays would soon become standard in clinical care 1 .
Perhaps the most transformative potential of bioinformatics lies in shifting healthcare from being reactive to predictive and preventive.
"By using individual genetic information to prevent, diagnose earlier, and treat disease/cancer with better precision, this type of genomics-enabled medicine promises health care that is personalized, more predictive, and preventive rather than reactive" 1 .
This vision extends beyond human medicine to agriculture, environmental science, and industrial biotechnology. From developing disease-resistant crops to engineering microorganisms for environmental cleanup, the computational approaches showcased at MCBIOS have broad applications that address some of society's most pressing challenges.
The 2015 MCBIOS conference showcased a field in rapid transition, where computational power and biological insight were converging to create unprecedented opportunities for understanding and engineering life. From award-winning methods that make research more efficient to practical applications in cancer treatment and crop development, the work presented demonstrated both the current impact and future potential of bioinformatics.
What makes this progress particularly exciting is its collaborative nature. As one article would later note, computational researchers increasingly collaborate with experimental researchers, with some even establishing their own experimental labs to test computational predictions 7 . This synergy between computation and experimentation accelerates discovery, as each approach informs and refines the other.
As we look to the future, the emerging trends highlighted at that 2015 conference—precision medicine, integrative genomics, sophisticated network analysis—have only grown more relevant. The code of life remains complex, but with increasingly powerful tools to read and interpret it, we're moving closer to a world where we can not only understand that code but use it to improve health, agriculture, and our environment. The work showcased at MCBIOS represents important steps on that journey—a journey that promises to transform how we understand and interact with the biological world around us.