Computational Life Sciences & Informatics


Core Technologies


Contact Information

Bindley Contact
Charles Buck, Ph.D
cbuck@purdue.edu
Office 49-42208
BIND 206

Faculty Contact
David M Umulis, Ph.D
dumulis@purdue.edu
Office 49-41223
ABE 225

Additional Resources

Cyber Center
ITaP Research Computing
e-Enterprise Center
Envision Center
ICDS
PiiMS
Rosen Center
Statistical Bioinformatics Center
Statistical Consulting Services

Overview

What is Computational Life Sciences and Informatics (CLSI)?
Computational Life Sciences and Informatics is one of the most important and exciting areas in all of science and technology, as it is positioned at the intersection of modern biology, quantitative modeling and high performance computing. It focuses on the development and application of computational tools and techniques to solve complex problems in biosciences. CLSI helps provide fundamental understanding of complex biological systems and offers the potential to significantly impact a wide variety of technologies, including drug discovery, novel therapies for human, animal and plant diseases, metabolic engineering and efficient production of traditional and high-value foodstuffs. Research in Computational Life Sciences and Informatics (CLSI) at Bindley Bioscience Center focuses on understanding (and predicting) life using a "Systems Biology" approach. Systems Biology aims at system-level understanding of biological systems, through which the "group of parts" that make up "the whole" are connected one to another and work together. The ultimate goal of Systems Biology is to develop in-silico bio systems. As a complex discipline, Systems Biology acquires data from all biological fields, including genetics, biochemistry, structural biology, cell biology, physiology, and biophysics; and through the use of mathematical models, regulation and communication pathways and relationships among the components in hierarchy from DNA to individual organisms can be established.

Computer science research contributes methods and tools for acquiring, storing, organizing, archiving, analyzing and visualizing biological data and phenomena. In addition, the management and mining of large databases of bioinformatics data must also be achieved. Computational Life Sciences and Informatics can be divided into three major categories:

  • Bioinformatics: The research, development or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.
  • Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.
  • Systems Biology: The development of quantitative, mechanistic based models of the whole cell, collections of cells or large pieces of the cellular machinery, where the objective is an integrated picture that compliments the reductionist viewpoint of molecular biology.

Efforts thus far have been focused on the Purdue Discovery Pipeline project (see below). For more information about this comprehensive project, click here.

pipeline

CLSI Developments


Software developed in BBC
  • XMass
  • XAlign
  • PepGo
  • SysNet
  • MetAlign
  • MetPP (under development)

Other commercial software

LIMS (Laboratory Information Management System)

Infrastructure

Life sciences research within Purdue and with external collaborators is supported by the Bindley Bioscience Center with the Computational Life Sciences Data System (CLSDS). This system is designed to:

  • Capture all information from wet experiments to data analysis;
  • Automatically transfer data into a central data archival system;
  • Enable web access for data mining; and
  • Gain data format standardization.

The BBC network infrastructure includes two major interconnected areas: an instrument farm and a data farm. The instrument farm consists of research instruments and computers used for instrument control and data collection. Data gathered from research instruments is automatically stored on BBC servers and the BBC Storage Area Network (SAN). This data farm is the back end of the BBC network that handles data storage and backup, as well as data access. The data farm provides a centralized storage location of research data that can be accessed by BBC scientists as well as collaborators from other universities and institutions. Each server and device in the data farm is covered by a backup solution that provides a second copy of research data in the event of data loss or corruption. The data farm is also accessible via a number of analysis workstations. These workstations are used to process and analyze the gathered data using the Purdue Discovery Pipeline and other statistical tools.

Infrastructure

Resources

The Computational Life Sciences & Informatics (CLSI) core of the Bindley Bioscience Center interacts closely with many other related groups at Purdue University to provide an integrated environment for a number of goal-oriented, cyber/computational activities on the Purdue campus:

Discovery Park's Cyber Center Overview

The Cyber Center creates human infrastructure for collaboration and research projects engaging cyberinfrastructure at Purdue. Based on distributed computer, information, and communication technology, the Cyber Center engages in basic cyberinfrastructure research, development of new cyberinfrastructure tools and techniques, and deployment of results to real communities meeting real user needs at Purdue and beyond. The center's co-location and shared research objectives are powerful drivers in the development of new technology, new discoveries, and new businesses, resulting in start-up businesses, new jobs, and economic development.
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e-Enterprise Center Overview

Discovery Park's e-Enterprise Center (e-Center) engages in research in the goal-oriented application of digital technology to business, government and societal problems. It also provides infrastructure and an integrated environment for a number of goal-orients, cyber/ computational activities on the Purdue campus, with a special focus on areas where Purdue has, or can develop, national leadership. The e-Center brings together faculty and students with strengths in modeling, simulation, optimization, database systems, software engineering, information security, communication, management, algorithm engineering, operations research, production systems, decision theory, system analysis, risk management, marketing, and customer service
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Envision Center for data Perceptualization Overview

Researchers in the Envision Center for Data Perceptualization explore novel computer graphics, advanced visualization, and human computer interface technologies, such as auditory, haptic, and multimodal interaction. These technologies are integrated with state-of-the-art advanced computation and networking, and high-end immersive visualization environments to assist researchers and industry in their quest for new knowledge and innovative products. The center's aim is to enable the development and practical application of collaborative perceptualization science, with a focus on the research, development, integration, and evaluation of high-end technologies and systems that extend and complement commercially available tools.
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Indiana Center for Database Systems (ICDS) Overview


Indiana Center for Database Systems (ICDS) at Purdue University is a leading database research center conducting research in a variety of topics including multimedia databases, data mining, data streaming and sensors, database security and privacy, knowledge bases, web services, data integration, data uncertainty, bioinformatics, and medical informatics. In addition to conducting fundamental research, ICDS strives to move research towards practice through projects in digital government, healthcare, telemedicine, and telemaintenance. The facilities of the ICDS and Purdue's Department of Computer Sciences are operated by technical staff who are not only responsible for the installation and maintenance of the systems, but also assist faculty and students in the development of software systems for research projects. The staff includes a director, facilities manager, administrative assistant, one network engineer, one hardware engineer, six system administrators, and several student assistants.
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Information Technology at Purdue (ITaP) Research Computing Overview


Established in 2001, ITaP Research Computing supports data and numerically intensive research applications on high performance computing systems, such as Purdue's IBM SP and the DXUL archival storage system. It also provides training and technical support in areas including scientific programming, program design, optimization, and parallel programming. This group provides the information technologies and maintenance service for the Bindley Bioscience Center's CLSI. High performance and data intensive computing resources available to researchers include an IBM SP supercomputer, PC clusters, distributed computing solutions, and mass data storage. The clusters and SP provide an aggregate capability of 1.75 teraflops. ITaP is currently adding additional resources that will increase the aggregate capability to 3.9 teraflops. In addition, the Purdue SP is linked by way of the I-Light high-speed optical fiber connection(currently 1 Gbps) to the IBM SP supercomputer at Indiana University to provide an additional 1+ teraflop-distributed terascale computing capability.
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Rosen Center Overview

The Rosen Center for Advanced Computing coordinates and provides high performance computing, scientific visualization, remote sensing satellite data, and TeraGrid services to researchers at Purdue University. Center staff provide training and initial assistance in using facilities and resources. This group also collaborates with faculty on research proposals and provides copy describing ITaP resources for proposals.
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Statistical Bioinformatics Center Overview


The cycle of theory, experiment, and information is nowhere more important than in the life sciences, where we are learning how to piece together various levels of expertise into a global or systems-level understanding of biology. Statistical Bioinformatics is involved at each level: accumulation, organization, and analysis of biological data. Hypotheses that are initiated and tested can be refined, and new experiments formulated for the purpose of supplying more information.
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Statistical Consulting Service (SCS) Overview

The Department of Statistics provides statistical software and design consulting services for the University community. Faculty, students and staff are encouraged to use these services, which are offered free of charge.
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Purdue Discovery Pipeline

pipeline

About Bindley

Interdisciplinary life sciences and engineering researchers collaborate to explore new technologies and scientific knowledge that impact the broad boundaries of plant, animal, and human diseases.

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Bindley Bioscience Center
1203 W. State Street
Purdue University
West Lafayette, IN 47907-2057