Organization profile

The Carl R. Woese Institute for Genomic Biology (IGB) is an interdisciplinary institute dedicated to transformative research and technology in life sciences using team-based strategies to tackle grand societal challenges. Members conduct genomic research in the areas of food security, energy, health, technology, and environmental conservation within collaborative research themes. These themes draw faculty from many schools and departments, including biology, chemistry, physics, engineering, sociology, and business, who remain an integral part of their home departments while also pursuing research at the IGB.

In each theme, the common goal of a particular grand challenge in research—developing more effective cancer therapeutics, creating more efficient and robust food and fuel crops, uncovering the origins of life—creates synergy among diverse groups of scientists. Our work ranges from basic research that expands the horizons of human knowledge to applied research that builds on this foundational knowledge to create new technologies. The IGB’s complement of research themes is dynamic, adapting to new discoveries, methods, and needs.

Fingerprint The Elsevier Fingerprint Engine mines the text of the experts' scholarly documents – publication abstracts, awards, project summaries, patents, and other sources – to create an index of weighted terms which defines the text, known as a Fingerprint. By aggregating and comparing Fingerprints, the Elsevier Fingerprint Engine enables users to look beyond metadata and expose valuable connections among people, research units, publications, and ideas.

Genes Medicine & Life Sciences

Genome Medicine & Life Sciences

Proteins Medicine & Life Sciences

Enzymes Medicine & Life Sciences

Peptides Medicine & Life Sciences

Bees Medicine & Life Sciences

Escherichia coli Medicine & Life Sciences

Zea mays Medicine & Life Sciences

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Profiles

Elizabeth Ainsworth

Crop Sciences - USDA Agricultural Research Service Scientist
Plant Biology - Adjunct Professor
Carl R. Woese Institute for Genomic Biology - Institute Affiliate

Person: Academic

Aleksei Aksimentiev

aksiment@illinois.edu

Physics - Professor
National Center for Supercomputing Applications (NCSA) - Professor
Carl R. Woese Institute for Genomic Biology - Affiliate
Bioengineering - Professor
Beckman Institute for Advanced Science and Technology - Professor

Person: Academic

Brian F Allan

ballan@illinois.edu

Entomology - Associate Professor
National Center for Supercomputing Applications (NCSA) - Associate Professor
Carl R. Woese Institute for Genomic Biology - Affiliate

Person: Academic

Research Output 1969 2019

¹³C-lutein is differentially distributed in tissues of an adult female rhesus macaque following a single oral administration: a pilot study

Jeon, S., Li, Q., Rubakhin, S., Sweedler, J. V., Smith, J. W., Neuringer, M., Kuchan, M. & Erdman, J. W., Jan 1 2019, In : Nutrition Research. 61, p. 102-108 7 p.

Research output: Contribution to journal › Article

Lutein

Macaca mulatta

Oral Administration

Tissue Distribution

Haplorhini

AcMC ²: Accelerated Markov Chain Monte Carlo for Probabilistic Models

Banerjee, S. S., Kalbarczyk, Z. T. & Iyer, R. K., Apr 4 2019, ASPLOS 2019 - 24th International Conference on Architectural Support for Programming Languages and Operating Systems. Association for Computing Machinery, p. 515-528 14 p. (International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access

Markov processes

Particle accelerators

Program processors

Field programmable gate arrays (FPGA)

Application specific integrated circuits

A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection

Saboo, K. V., Varatharajah, Y., Berry, B. M., Sperling, M. R., Gorniak, R., Davis, K. A., Jobst, B. C., Gross, R. E., Lega, B., Sheth, S. A., Kahana, M. J., Kucewicz, M. T., Worrell, G. A. & Iyer, R. K., May 16 2019, 9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, p. 323-327 5 p. 8717057. (International IEEE/EMBS Conference on Neural Engineering, NER; vol. 2019-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Electroencephalography

Learning systems

Data storage equipment

Electrodes

Set theory

Datasets

NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees

Molloy, E. K. (Creator), Warnow, T. (Creator), University of Illinois at Urbana-Champaign, Jul 29 2018

DOI: 10.13012/B2IDB-1424746_V1

Dataset

Data from: The Performance of Coalescent-Based Species Tree Estimation Methods under Models of Missing Data

Nute, M. (Creator), Chou, J. (Creator), Molloy, E. K. (Creator), Warnow, T. (Creator), University of Illinois at Urbana-Champaign, 2017

DOI: 10.13012/B2IDB-7735354_V1

Dataset

Using INC within Divide-and-Conquer Phylogeny Estimation - Datasets

Rao, S. (Creator), Zhang, Q. (Creator), Molloy, E. K. (Creator), Sy, A. (Creator), Le, T. (Creator), Warnow, T. (Creator), University of Illinois at Urbana-Champaign, Jan 24 2019

DOI: 10.13012/B2IDB-8518809_V1

Dataset