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Exploring Bioinformatics at SBMI


Arif Harmanci, PhD, MS

Thursday, May 31st, 2018

“Biology + Computers = Path to a great interdisciplinary career in biotech and pharma.”
- Arif Harmanci, M.S., Ph.D.

SBMI’s bioinformatics track is the perfect venue to jumpstart a career in biotechnology, no matter what your background is. As a scientist who trained as an electrical engineer, I have firsthand experience in switching into the field of bioinformatics. SBMI is one of the best places to make this shift for yourself.

Let’s briefly look at what bioinformatics means. In general, biology seeks to understand how living things work and evolve. In the earlier days of biological research, methods were considered “low throughput.” Scientists tried to understand the cause of diseases using a limited amount of data. The analytical methods to analyze these data are well established by biostatistics. Recently, the data acquisition techniques have advanced exponentially and made it possible to generate billions of measurements from each individual, every day. Sifting through this data to make it useful for health is an enormous data science problem. This is where bioinformatics comes in.

Bioinformatics uses computers to help explain complex biological phenomena. By itself, this makes perfect sense because a cell is an extremely complicated network of interactions between chemicals. The flow of biological data through these networks is what aids an organism as it lives its life. From that perspective, the distinction between health and disease is merely about the body’s ability to process information appropriately. Disruption of these information processing networks puts the body at risks of getting diseases such as cancer or autism. Although the manifestation of the diseases is very distinct and different from one another, the cause of any disease ultimately points to one or more malfunctioning network.

Bioinformatics combines multiple layers of information, for example, measurements of genetic, imaging, proteomics, microbiomics, etc. in very large quantities. It is a data-driven endeavor meant to understand and cure disease. Thanks to the plethora of data resources at SBMI, we can incorporate disparate data sources such as electronic health records as well. As we gather different data types, we will be able to look at our information processing networks in more detail to ultimately diagnose and treat diseases better.

What is the Relationship between Informatics and Data Science?


Wednesday, August 2nd, 2017

When examining the connection between informatics and data science, the ratio is rather simple – 1:1. Informatics is the equivalent of data science.

Informatics = Data Science Infographic

Biomedical informatics is an amalgam of data science with both biomedicine and health components added in. Data science is a recent name that grew out of the emergence of big data, although biomedical informatics, i.e., data science in biomedicine and healthcare, has been around for several decades. The field of biomedical informatics is also an interdisciplinary field that involves:

  • Clinical science and practice: medicine, nursing, dentistry, pharmacy, population health
  • Public and community health
  • Computer science and engineering: database, algorithm, programming, artificial intelligence, machine learning (including deep learning), neural network, cognitive computing, distributed computing, cloud computing, natural language processing and text processing, security, visualization, mobile devices, sensors, internet of things, etc.
  • Cognitive science
  • Mathematics and biostatistics
  • Social and behavioral sciences
  • Management science
  • Health information technology policy and legal issues

Within biomedical informatics, there is an emphasis on certain key processes; acquisition, storage, communication, processing, integration, analysis, mining, retrieval, interpretation, and presentation. These processes transform data to information to knowledge to intelligence; these are entities.

Once researchers have entities for evaluation, the next step is to perform descriptive, predictive, and prescriptive tasks or functions. In general data science or informatics, these processes, entities, and functions can be applied to any domains. For biomedical informatics, the application domains are biomedical discovery, healthcare delivery, and disease prevention.

Focusing on innovations in these processes, entities, and functions, faculty, students and researchers at SBMI are performing in-depth research studies within the field of data science in biomedicine and healthcare.

Let’s take a closer look at how this framework works:

  • Data is unintepreted, unprocessed, meaningless raw symbols, signals or pixels. For example, “101” could mean several things; the decimal number one hundred and one, the binary number five, the values of three pixels or even a label for a highway. Without context, most data types are meaningless.
  • Information is interpreted data or data with meaning. For example, once we know that the metric for 101 is degrees in Fahrenheit, we immediate correlate the number to temperature. Information provides a descriptive function and tells you what happened, at what juncture and for whom.
  • Knowledge is organized information that is justified or validated. Let’s say that we also know that 101 °F is an adult oral temperature. Immediately, we know that this indicates an abnormal body status (fever) and this relation is validated in medical practice and research. Knowledge provides a predictive function and tells you what might happen. An adult oral temperature of 101 °F predicts that the body status is irregular.
  • Intelligence is actionable knowledge. An adult with a 101°F temperature should take fever medication, have further assessment and diagnosis performed and may need to see a doctor if it is not a simple cold. Intelligence provides prescriptive function and tells you what needs to be done. 101 °F adult oral temperature prescribes the action of taking fever medicine and further assessment.

SBMI Heads to Orlando for HIMSS17


Wednesday, February 15th, 2017

Collaboration for Population Health Improvement Initiative


Wednesday, November 23rd, 2016
written by James Langabeer, PHD

  • Hello SBMI Community-

    As part of a UT System-wide initiative, UTHealth has engaged in a comprehensive planning process to explore and improve the health status for the communities that surround us. As a faculty member here at SBMI, I was lucky to have been chosen to lead this initiative. So, a question I get asked all the time is this: what is population health? Although many people think it’s the same as public health, it is not. I define population health this way:

    Population Health Continuum of Services covers Education, Clinical Care and Financing, Population Research and Human Resources

2016 AHIMA Convention & Exhibit Heads to the Charm City


Wednesday, October 12th, 2016

Celebrating National Health IT Week


Thursday, September 29th, 2016

A Ransomware Epidemic And An Overdue National Health IT Safety Center


Wednesday, August 17th, 2016:
written by Dean Sittig and Hardeep Singh

Five Reasons You Should Care About Health Care Informatics


Wednesday, June 29th, 2016

The Precision Medicine Movement


Wednesday, June 22nd, 2016

Where Can Health Informatics Take You?


Wednesday, June 8th, 2016

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