<p>anyone have any info/experience with this career?
and which of the two would be best? Comp eng undergrad--> bioinformatics MS? or biomedical eng undergrad--> bioinformatics MS? hmm or even chem eng...idk, help?</p>
<p>I don’t have any personal experience with Bioinformatics, but I do know someone in a biostatistics PhD program. His undergrad was in math. I think a more math and programming-based undergrad would benefit you in bioinformatics. Out of the choices you gave, I would go with computer engineering.</p>
<p>With engineering, I think he’s better off with bimolecular engineering.
With science, computer science, math, or biochemistry…</p>
<p>Just after browsing through a few sample curriculum…</p>
<p>Going off the UMich undergraduate curriculum (they have an undergraduate Bioinformatics program) you will need more math/programming classes than bio-type classes.</p>
<p>The following is my opinion based on spending a large part of my career working in bioinformatics. Others may have different opinions based on their experiences and, as always, YMMV.</p>
<p>First, note that bioinformatics requires both the biology and the computer science/engineering: the former to provide the problems to be addressed, the latter to provide the computational approaches for addressing the problems.</p>
<p>Both biology and computer technology are rapidly evolving fields, and bioinformatics is as well. In the beginning, bioinformatics was mostly (entirely?) focused on (1D) sequence analysis. Today, it also encompasses management of 3D structural information, analysis of complex data sets such as gene expression profiles of all of the expressed genes in a cell or tissue, computational simulation of whole cell processes, and more, with all of these avenues of attack being informed (and new avenues being opened up) by an increasingly sophisticated understanding of the biology. The computational tool box itself has grown from a focus on relatively straightforward string comparison algorithms to probabilistic models to highly complex machine learning algorithms, and from single processor computers to use of specialized processors (e.g. field programmable gate array processors) to use of sophisticated distributed computing strategies to leverage computing resources to maximum effect. </p>
<p>This rapid evolution means that the specific approaches you would encounter in a M.S. program could, as little as ten years out, be at risk for appearing quaint or even outmoded depending on how the problems and available technology evolve. (Hell, when I was a kid, molecular biology, genetic engineering, and the kinds of computers we have now were firmly in the realm of science fiction, never mind that, in my lifetime, I would be using them as <em>just another set of research tools</em>!) So, if go into bioinformatics you want to be a lifetime learner to keep up with the changing field or you risk obsolescence and unemployment. I think the best way to prepare for this reality is to make sure you have a solid grounding in the fundamentals of biology and computing. </p>
<p>Therefore, I would suggest using your undergraduate years to lock in a good understanding of the fundamentals. Either (1) major in biology (with a molecular/biochemical focus), and then supplement with a carefully considered set of computer science/engineering courses in your copious free time, or (2) major in computer science/engineering, and supplement with enough biology electives so that you understand the scientific problem domain that is addressed by bioinformatics. I don’t think a double major in computer science and biology is necessary to get adequate exposure to both; you should be able to find schools whose requirements will let you major in one and still have enough room in your schedule to do sufficient amount of the other. Then, finish off with the M.S. in bioinformatics to get a focused exposure to the current state of the art so you can launch into your career. You’ll hit the ground running with all the latest toys and approaches, but you’ll also have the fundamental background necessary to evolve and grow in the directions you choose as the field itself evolves and grows.</p>
<p>Additional comment: whether you emphasize the biology side vs the computation side via choice of major will depend on the particulars of your interests, aptitudes, previous exposures, etc. If I had to make a blanket recommendation, it would be that you emphasize the computational side and do a computing major and supplement with biology, but I hesitate to claim that’s the undisputable best approach for everyone. There’s a spectrum of activities in bioinformatics, some closer to biology, others closer to computer science, and you should think about whether you want to be towards one end, or towards the other, or smack dab in the middle. To put the question another way: do you think you’d like to be a biologist who works on the kinds of problems that are well serviced by computational approaches, and therefore want to make sure those are in your toolkit, or do you want to be a computer scientist or engineer who attacks interesting computational problems that emerge from problems in biology, and therefore want to have enough of an understanding of biology to make use of it in designing computational solutions, or perhaps even have the wherewithal to find interesting and relevant computational problems yourself? Or do you really want to be a “bridge” person who can wander with ease between the two and communicate with people on both sides? </p>
<p>Another additional comment: Your question implied that you would stop at a master’s degree and not go for a Ph.D., so I presume that means you’re not angling to work in the pure bioinformatics research space. You will need to see a lot of the topics that are traditionally under the “computer science” banner regardless (algorithms, database theory, etc), but in addition if you’re planning on working in the applied space I recommend you get exposure to some of the topics that lie under the “computer engineering/software engineering” banner (requirements definition, software development, best practices, etc.) because that’s going to be an important part of your workaday life. Warning: don’t take the name of a department or major (e.g. computer science vs computer engineering) as the final determinant of what you’ll have to see or will be able to see in that program. Always drill down to the specific course requirements and offerings to see what you can actually do. The exact name of the department/major is not important; grad programs and employers will make their decisions based on what you actually did in coursework, not on what some registrar’s office calls it.</p>
<p>Another further additional comment: undergraduate programs that specialize in bioinformatics are becoming available, I believe. I’d consider those a viable path too, as long as the focus of the program at the interface of biology and computation doesn’t come at the expense of a thorough grounding in the basics. It will do you no good to come out of a bioinformatics program as an expert in hot technology A, B, and C, if several years later X, Y and Z are the new hotness, but you’re unable to add them to your toolkit and use them effectively because you don’t have a grasp of their foundations.</p>
<p>Final further additional comment: unless someone says differently here, I don’t think biomedical engineering would fit in with your aims (unless that’s the flag under which a school has put a new bioinformatics program, which frankly I’d find odd, but maybe that’s just my prejudice). And I’m almost certain that chemical engineering is a wholly different beast altogether wherever you’d go. Specific advice: review existing graduate bioinformatics programs, see what they look for in successful applicants, and use that information to determine what you’ll need to do.</p>
<p>wow thank you! that was informative.</p>