SciLink Blog

Tom, Can you tell us a little about your background? how did you get into science and interested in a system’s approach?

As an undergrad at the University of Wisconsin I pursued dual interests in biology and English literature. I came across Lynn Margulis and Dorian Sagan’s Microcosmos, a wonderful treatise on the role of symbiosis in eukaryotic evolution, and wanted to pursue a few ideas on the putative bacterial origin of the structural protein tubulin. Fortunately, I was at Wisconsin during the late 1980’s, which was a great place to be during the seminal years of bioinformatics. Two pioneering sequence analysis software companies, the Genetics Computer Group (GCG, currently Accelrys) and DNASTAR, sprang out of efforts to sequence Escherichia coli at Wisconsin; GCG by John Devereaux and DNASTAR by Fred Blattner. With this backdrop I began to pursue my nascent ideas in sequence analysis and symbiosis.
I completed an undergraduate thesis on the molecular evolution of tubulin under the guidance of Dr. Gary Borisy (an expert in tubulin and cell division) and Dr. Ann Palmenberg (an expert in RNA picornaviruses). Ann taught and organized a seminar series in Bioinformatics, which was likely among the first classes in the country. She worked with John Devereaux to bring in many of the heavyweights in Bioinformatics; both for the seminar series and to collaborate with GCG. I took the class three times and was taught early sequence analysis theory by Michael Zucker (RNA folding), Steven Altschul (BLAST), Temple Smith (Smith-Waterman alignment), Walter Fitch (molecular phylogeny), James Crow (neutral theory of evolution) and many others. The undergraduate thesis did not lend itself to any spectacular results, presumably due to a combination of my inexperience, an exceedingly small database of protein sequences (Genpept was around 40,000 sequences in 1990) and the lack of a structure-based phylogenetic approach. Later, Linda Amos and Jan Löwe, would show that there was indeed a strong structural similarity between tubulin and bacterial ftsZ structural proteins, although symbiosis may not needed to explain this event as later transfer is just as likely.
My undergraduate work did, however, give me a taste of bioinformatics and sequence analysis which would lead me to Boston University and BG Medicine. After graduating Wisconsin, I took a role at DNASTAR in sales and technical support and shortly transitioned into technical writing. After a time I grew tired of describing bioinformatics tools and wanted to develop and apply them myself. With Fred Blattner’s (head of the E.coli genome project and DNASTAR’s founder/CEO) encouragement and support I joined Temple Smith’s group—the BioMolecular Engineering Research Center (BMERC)—in the fall of 1996.

Tell us a little about your experience in graduate school and your interest in bioinformatics

I was again extremely fortunate to be at the BMERC during the late 1990s. The lab had a number of research interests, anywhere from sequence analysis (dynamic programming, Bayesian prior-profiles) to protein structure prediction (homology modeling, threading) to molecular phylogeny. The Institute for Genomic Research (TIGR) was beginning to rapidly complete multiple bacterial genomes and eukaryotic genomes were in sight. This afforded a tremendous opportunity in comparative sequence analysis. Under Temple’s leadership and an extremely bright group of post-docs, students and collaborators we were able to accomplish a lot of guerilla science (get in, make your mark, get out before the big-boys arrive), including a technical comment in Science on Genome Excess plots in my second year in the lab.
The environment at BMERC was quite different than many graduate experiences. Temple encouraged debate at all levels and collaboration within and outside of the group. He can still beat most of his students with a gigantic library of existing codes (“I’ve already done that in Fortran…”). His piped combinations of Sed, Awk, Sort and Comm are still semi-legendary.
I finished my dissertation work applying prior-profile analysis to proteins involved in mitochondrial pathologies. This work highlighted the great degree of sequence and structural conservation among the mitochondrial proteome and the consequences for modifying key residues in critical locations.

After BMERC you joined Beyond Genomics now BG-Medicine what do you do there?

After graduating I joined Beyond Genomics, a Waltham, Massachusetts based systems biology start-up. In those days BG was more of a technology shop interested in developing mass spectroscopy approaches to measuring systems, primarily in plasma. We also did a lot of work developing the computational, statistical and bioinformatics architecture necessary to support such efforts. Eric Neumann (Clinical Semantics Group), Matej Oresic (VTT, Finland) and I created correlation networks as a way to take advantage of mathematical associations in cross-omics data. The key advantage of such an approach is the ability to annotate and understand poorly-characterized analytes as well as well-characterized analyte within the context of a single experiment. This approach became extremely useful in evaluating novel mechanisms of disease development and drug interaction, biomarker discovery and circulating biomarkers of tissue effect.
I took over leadership of the group from 2003-2006 and have since moved on to direct the project planning & data interpretation group at BG Medicine (Beyond Genomics changed its name to BG Medicine in the fall of 2004). In this role I have greater responsibilities for experimental design as well as the back end of bioinformatics and general biocontextualization (a fancy systems biology term for attempting to place findings into an appropriate biology context). This included primary scientist roles in our Liver Toxicity Biomarker Study (LTBS) and our High-Risk Plaque consortium (HRP).

What you believe is the definition of system’s biology and how a system’s approach will aid clinicians and pharma in getting to a diagnosis and treatment?

Hiroaki Kitano, Lee Hood and Doug Lauffenburger still have the best definitions for Systems Biology. From Kitano’s review in Science in 2002 he described systems biology in terms of four properties: system structures, system dynamics; the control method and the design method. This view is fairly complementary to Lauffenburgers’s 4M model: measure, mine, model, manipulate. The problem is that, with the exception of very narrowly defined systems, we’re still in the first two stages: measuring all of the omics data you can and trying to determine the relationship among the measured analytes. Having a good understanding of network control and manipulating networks is still a ways, off, at least for most of the problems that clinicians and the pharmaceutical industry is interested in. A few companies (Entelos, Genstruct) are focused on this problem but most of this work is still carried by academics. Some groups are combining systems biology alongside synthetic biology, for example Jim Collins’ and Tim Gardner’s work on mammalian switches and network inference, which look particularly promising.
BG Medicine has taken a more narrow approach in the systems biology space focusing on ‘Systems Pathology’ and ‘Systems Pharmacology’. Systems Pathology is loosely defined as the measurement and interpretation of molecular analytes that change in the disease state. Systems Pharmacology, then, is the measurement and interpretation of molecular analytes that change with a pharmacological perturbation. Under this model measuring system components and their interactions are the keys to elucidating a system under disease burden and drug treatment.
In terms of the ultimate utility of system approaches for medicine, I’d stress the importance of well-conceived experimental designs over sophisticated pathway, network and bioinformatics approaches—yes this is coming from a card-carrying bioinformaticist. So many of the omics studies today are underpowered, making results non-generalizable to larger contexts. Good experiments are costly, however, so this is why small sample sizes are the norm. We spend a lot of time reviewing project objectives prior to carrying out any experiments: is the study sufficiently powered to see univariate markers? Multivariate classifiers? Correlations among analytes? Are we recording the system with the right set of experimental platforms to measure perturbations in disease and drug intervention? Even addressing these concerns there are still a lot of open questions that can interfere with interpretation. Are you measuring at the right time-scale? In the right location? Do you need to fractionate tissues or cells? Does a cell-system accurately recapitulate its environment? Does an animal model accurately recapitulate clinical behavior? I could go on…
The first return on investment using a systems approach will probably occur at the intersection of systems biology with biomarker discovery, likely on the diagnostic front. Biomarkers derived from omics experiments are already in use for disease classification, such as Oncotype Dx® for breast cancer. Therapeutic response is another area where biomarkers can play a role. Predicting responders/non-responders when the disease and drug treatment is known is a much less parameterized space than disease classification and therefore a less daunting target. The holy grail for biomarker utility is an analyte, or small set of analytes, that can be used for diagnosis, prognosis and therapeutic monitoring, for example; this marker would be elevated in diseased individuals over healthy, higher levels indicate a poorer prognosis and drug therapy would decrease biomarker levels over time while outcome improves. Biomarkers of this type are exceedingly rare and to my knowledge, only Galectin-3, a prognostic marker of hear failure, comes close.

Who should reach out to you in SciLink?

I have two primary interests, one in network biology and pathway analysis and a second in biomarker-guided medicine (the ‘BG’ in BG Medicine). I
Some of my thoughts in network biology are better suited for an academic environment, and I hope to develop these further at Northeastern (these concepts were recently published in Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools: “Systems Biology, Biomarkers, and Biomolecular Networks”). I’m always interested in bouncing these ideas off like-minded colleagues.
Biomarker adoption throughout the entire therapeutic process is slowing becoming a standard approach. There is a chain of biomarker utility from disease prediction, disease diagnosis, disease prognosis, disease classification, therapeutic selection, therapeutic predictors of response/nonresponse and well as surrogate biomarkers. I’m also interested in discussions around the use of biomarker-guided therapies at both the scientific and business level.

See Tom’s Profile On SciLink

In the United States today more patients are having elective surgical treatments than ever before, 32.7 million in year 2006. Surgical innovations have made not only the recovery process quicker but as many as 75% of the elective procedures done today are done as outpatient procedures. Comprehensive perioperative risk assessment and focused postoperative medical management are increasingly becoming an integral and indispensable part of quality surgical care today.

The average surgical patient today can be older and more obese. Preoperative medical complications are common in patients of advanced age and those with co-existing medical conditions like hypertension, diabetes, heart disease and obesity, just to name a few. These complications worsen surgical outcomes and increase the cost of care. As perioperative patient care protocols expand to include a wide variety of medical morbidities, some clinicians with traditional medical or anesthesiology training feel unprepared to serve as medical consultants for or co-manage surgical patients. At the same time awareness of newer risk factors for postoperative complications with increasing age and obesity is important.

Meet Roop K Kaw MD, an Assistant Professor with the Cleveland Clinic Lerner College of Medicine and Department of Hospital Medicine, Medicine Institute, at the Cleveland Clinic. He recieved his medical degree from the University of Kashmir, India in 1990. He is board certified in Internal Medicine and an associate of the American College of Physician Executives.

He is actively involved in research in the area Perioperative Medicine and Outcomes. His current research focuses on novel predictors of cardiopulmonary risk in patients undergoing major surgery. Dr Kaw is currently funded by the NINDS (NIH) for studying the incremental risk of Sleep Apnea in cardiac surgical patients and the role of Crystal-20 monitor in inpatient Sleep studies. Dr. Kaw is widely published and serves on the editorial board of several medical Journals. He has presented his research both nationally and internationally.

Dr. Kaw serves on several national committees and advisory boards. He is a member of the Research committee for the Society of Hospital Medicine and co-chaired the scientific abstract committee in the 3rd Annual Perioperative Summit at the Cleveland Clinic. He also serves on the Advisory Board of Gerson Lehermans Council of Health Care Advisors and Reuter’s Insight an independent international research consultancy

Who should contact Dr. Kaw?

Anyone interested in Perioperative Medicine should join him on SciLink and also join the new Perioperative medicine group. See you all there!

Update

The SciLink Perioperative Medicine Group is growing:

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I had the pleasure of interviewing Carl Zimmer in early May of this year. I took a bit of pleasure turning the tables on this intriguing science writer, as you could imagine, he hadn’t been interviewed too many times in the past. Although my interview was brief, I was able to glance into Carl’s world and passion for science. We explored a number of topics from the mundane (what it takes to get into science writing) to the publishing industry and finally to his incredibly interesting book on E.coli. What I found most fascinating about Carl was his complete lack of salesmanship and ego. You see, Carl is known in science writer circles as a force to be reckoned with. The New York Times Book Review calling him, “as fine a science essayist as we have”. I imagined all kinds of different scenarios unfolding as I picked up the phone to dial Carl’s number: overbearing ego maniac, super being who was too busy and bored to take my call etc. But surprisingly, none of these scenarios played out. Carl Zimmer is soft spoken, often self deprecating and extremely generous with his time. No ego here, just a man with a passion for science and nature. And, yes, he’s wicked smart.

Here are some excerpts from our interview:

How did you get into science writing?
[I] was at Discover magazine, just trying to get in to magazine world.. Once I started there, I found out that I really enjoyed science writing, and I haven’t stopped since.

What is/was your favorite topic in science right now?
I’ve just written a book about E.coli. I guess you could call me E.coli’s missionary. The book tries to show how much cool biology is packed into such a tiny thing. It can sense chemical and temperature gradients and integrate this information as if it had a brain. It can use this information to navigate through its environment. Engineers are getting obsessed with E. coli because the way its genes and proteins interact reminds them of auto pilot systems. When you learn about E.coli [you’re] really learning about the entire history of molecular biology.

How do you feel about open access publishing like PLOS/BMC?

I blogged about this here. I believe that open access papers will get more coverage in old and new media than papers published in traditional subscription journals. There are huge time advantages in reading open access journals. I can Google for a topic and in 2 seconds can be reading the entire article. If I come across a paper in a closed journal, I can’t get it immediately. The extra steps involved will inevitably push people toward open access models.

Another factor playing in open access’s favor is that it doesn’t create pointless conflicts between a journal and the people who write about what’s in it. One striking example involved a blogger who had written about a paper sourced from a subscription journal: This individual reproduced a figure and got an email threatening legal action. This looked really bad for the publisher and [the] blogosphere revolted. If I write a piece that is sourced from a PLOS (http://www.plos.org) paper and reproduce a figure on my blog, I know I won’t be harassed.

Any pointers for other up and coming science writers?
People really need to learn how to write. Spend the time training through internships, graduate school, freelancing etc. You have to spend the time practicing your craft. This is a really interesting time to be a science writer but conventional opportunities are disappearing so try to be as creative as you can. Try to write every day whether you have an assignment or not. My best piece of advice is that no one can read your mind: Very few people have PhD’s in your area so start with that premise and the clarity of the story.

Who should reach out to you in SciLink?
I’m interested in connecting with Biologists and Earth Scientists who need help telling their story.

Check out Carl’s Publications:
My Book - Microcosm
My blog - http://www.scienceblogs.com/loom/
My website – http://www.carlzimmer.com

Brad Langhorst, 33, grew up in Denver, Colorado where his father worked for General Motors as an Engineer. During his junior year in high school, Brad’s father was transferred to Michigan where there was a gym requirement. Having played sports in high school, he had no gym credits and he didn’t want to spend his entire senior year in gym shorts. Cleverly, Dr. Langhorst looked for alternatives and found the School Year Abroad program in Barcelona, Spain that would allow him to finish high school and experience more of the world. After winning an appointment to the U.S. Naval Academy, Brad thought the curve-balls were behind him. But, in a strange twist of events, he lost his appointment due to a medical disqualification. Scrambling for another option, Brad applied and was accepted to Johns Hopkins University. After spending some time there Brad decided the famous JHU “pressure cooker” wasn’t for him and transferred to The University of Connecticut where he worked at the National Analytical Ultracentrifugation Facility. After UConn, Brad heard about the human genome project and thought “if I don’t participate in this it would be like living in the 60’s but not going to Woodstock”. He joined the genome project at the Whitehead Institute Center for Genome Research and deferred his grad school aspirations. After his stint at Whitehead working on gene-disease association studies he started a Ph.D. program at the University of New Hampshire to work in Tom Laue’s lab. To balance his long-term scientific goals with some more immediate impact on the world, Brad and some friends started CoopMetrics while in graduate school. By applying scientific data reduction and analysis techniques to financial data, CoopMetrics has been able to provide cooperatives of local businesses with analytical tools to help them compete with chains. Having just finished his doctorate and with CoopMetrics large enough to sustain its growth without his day-to-day input, Brad has begun his search for the next curve.

We had a chance to ask Dr. Langhorst a bit out his work and future as a newly minted Ph.D. in an economic downturn:

What interests you in Science?

While the first large scale step in understanding how life works is the genome project, as Eric Lander says: It’s just a parts list. Interactions between proteins and other molecules, as the major effectors of biology must be understood in detail if we are to move from tinkering to engineering. Projects like UniProt, HUGE and PRIDE are building the catalog of proteins and their interactions but don’t address the details of the interactions. The Research Collaboratory for Structural Bioinformatics collects structural information about proteins in the Protein Data Bank. Understanding the energetics of a molecular interaction under specific conditions is an inherently low-throughput endeavour but it is required if we are to tell the difference between interactions that effect change and those that are a result of happenstance. Only detailed studies of the individual interactions can provide sufficient detail to draw these important distinctions. If we can connect the large scale efforts mentioned above with the individual experiments on protein interactions performed in labs all over the world, we’ll be able to construct a valuable resource to allow someone to understand the entire network of interactions that takes place when Molecule X interacts with a protein. PANDaS (Protein Association Network Data Server) is the result of my dissertation work collecting Analytical Ultracentrifuge data and analyses, it is a first step toward my long term vision of understanding the entire network of important protein interactions in enough detail to make predictions.

What did you learn were your strengths in grad school?

Early in grad school, my family called me “5 projects”; I like to work in parallel to hedge against bad ideas, but at some point you have to focus on one to make real progress. In graduate school, I learned how to strike a balance between keeping options open and diving into the most promising option.

What are you looking for in your next career move?

I’d like to work with people doing large scale data discovery and integration. My dissertation work involved aggregating protein association studies and storing/analyzing them in a database. I’d like to use the analytical and informatics skills I honed in grad school in a new area during this next step. This was one of my main reasons for joining SciLink - to identify potential collaborators and/or employers who share my interest in understanding biology with enough depth to make intelligent interventions. I loved working at Whitehead where there was a collection of smart people with varied experience and interest working toward roughly the same goal. I’d like to find a similar experience.

So is that your dream scenario then?

My dream job would allow me to extend my dissertation work from Analytical Ultracentrifugation to other solution techniques like Surface Plasmon Resonance, Light Scattering, Calorimetry or Electrophoresis. I’ve built a framework tools to collect data and analyses but this is too big a project to complete on my own. I hope I can find a group of like-minded people who can fill in the gaps in my expertise benefit from my experience.

I guess you could call what you’d like to build the “Protopedia”?

I hadn’t thought of it that way but the idea is a lot like Wikipedia in that it concentrates the efforts of many scientists to build something valuable.

Who should reach out to you in SciLink?

I just finished my Ph.D. so I’m looking for opportunities where I can utilize my analytical and computation skills. Collaborators, recruiters in both academia and the pharmaceutical industry are welcome but I’m interested in connecting with anyone who shares my interest in understanding protein interactions.

Chavonne Jones, 24, always had a penchant for science and education. She recalls an early memory while in high school, “we were assigned a group project about something environmentally related. A NOVA program came on TV about genetically engineered foods. It was then that I became completely fascinated with genetics and genetic engineering.” She would go on to take part in many school activities seeking out ways to combine her love for science and education. It was those early days that helped shape Chavonne’s work and life’s passion: The education and dissemination of genetic information as a genetic counselor.

Chavonne enrolled in the genetics program at Nevada School of Medicine in Las Vegas where she has been for the past 2 years and runs the website, www.humangeneticsdisorders.com that, “is committed to genetics education awareness. To obtain a better understanding about genetic revolution, we provide the history of genetics. The latest information on all human genetic disorders from Achondroplasia to Wilson’s disease is available. Other areas of focus include: dna and rna sequencing, stem cell research and therapy, genetic testing and screening, genetic selection, genes and behavior, mental health, gene therapy, cytocogenetics, pharmacogenetics, xenotransplantation, cloning, ethical, legal, and social issues in medical genetics.”

Ms. Jones enjoys taking part in the Genetic Alliance – an organization dedicated to genetics education and participates in the American College of Medical Genetics and is interested in a variety of genetics oriented topics including: gene therapy, biotechnology, plant genetics cytogenetics and stem cell therapy.

Chavonne is specifically interested in reaching out to those who are working in these fields to help her translate current research and discoveries to those in need. To contact her, join her SciLink network by getting in touch with here.