What's it like to work in a field that combines biology and computer science? (ie. biotech, medical data analysis)
I'm a high school senior, and I am going to major in computational biology or bioinformatics in college. I want to know what kind of job opportunities there are for someone going into that field, and what those jobs are like. #computer-science #biology #biotechnology #bioinformatics #computational-biology
Students majoring in Bioinformatics can look forward to careers in the healthcare, biotechnology, and pharmaceutical industries, as well as research opportunities in universities and government laboratories. They will also be well-prepared to apply to dental or medical schools.
This is a growing field with enormous career opportunities at the Bachelor’s, Master’s, and Doctoral levels - demand is high for individuals with a combination of biological knowledge and computational skills.
Graduates of the program may find themselves creating databases for a gene discovery project, using computer modeling to characterize the structure and function of a newly discovered protein, employing computational models to predict the spread of disease, or helping manage and analyze data from clinical trials.
In this link you can have some job opportunities:
While gene sequencing and analysis might currently be the main focus in bioinformatics, the field is quite diverse and opportunities also lie in other areas.
Below are brief descriptions of some of the areas within bioinformatics that opportunities are arising are:
Sequence Assembly: This involves the use of sophisticated computer-based methods to assemble the thousands of fragments that make up the genome of an organism.
Genomic Sequence Analysis: This involves mapping out the regions of a genome that code for a particular protein’s production. It also involves mapping out areas of the gene that is clipped out or discarded.
Functional genomics: This is the process of determining the functions of genes and determining whether they would suitable for drug discovery.
Genotyping: This involves the discovery of disease causing genes and using that knowledge to identifying individuals who are susceptible to such diseases.
Proteomics: An offshoot of genomic studies, this is the study of the portion of a genome that is expressed in particular cells. This usually involves the use of micro-arrays and the results are entered in a database. This area is especially useful for drug and/or gene therapy.
Pharmacogenomics: Here databases of single nucleotide polymorphisms (gene mutations that cause particular disease states or increase/decreased sensitivity to drugs) have an important role to play in future drug development efforts and in the design of clinical trials.
Database Administration: This usually involves the design and maintenance of huge databases of genomic sequence and biochemical information. There is also the involvement in the development of intelligent search algorithms to search through the database and retrieve relevant information.
Best of Luck!
Daniela did a fairly good job restating the information on linked website sources but let me provide some insight, something thats missing from many publications, especially dated ones.
Bioinformatics will often fall into the computer science department at most schools which comes with its own sets of pros (rigorous major, heavy recruitment by firms) and cons (not part of the engineering school which get more funding, require core curriculum outside of your intended major).
While Daniela's list covers definition based categorization of job prospects, it is important to see where the marketplace is moving to understand which of those options will be most widely available upon your graduation. Genomic sequencing and genotyping are two of the most widely studied fields within genetics at the time. They are evolving heavily as research towards personalized healthcare is getting more funding and greater attention. As a passionate student, you should look into those under a magnifying glass.
Research based jobs applications, whether it is for a corporation or a research university, will most likely be the type of institution you can work for. There are companies with related projects going on at most research universities like Drexel, UCLA, Duke and big companies like Theranos, Google, IBM and Palantir.
Apologies for the late response. I did not see the comment until now. The below is in response to your comment. My answer is too long to fit in the comment body, so I am posting this as an add-on answer.
The Broad Institute is a lovely place to work. I was there before being recruited to Mass. General Hospital. They do have an internship summer program, http://www.broadinstitute.org/diversity/summerprogram, though I do not know the details of it. (As you can see, the website is a bit outdated too.)
I do not know about the practicalities of a gap year, having never taken one myself. I do know that start ups are a tricky thing, having been in one. Usually a small start up hires more experienced personnel to build the company. In any case, if you are hired at one and are getting stock (even if not a publicly traded company), please make sure beforehand to really look into when to exercise your stock and the taxation of stock. People are often unpleasantly surprised by the details. There are other matters too. Please take a look at the answer to this question:
What is more important knowing whatever programming languages and databases is what you have done with them. Did you create some project with them? The demonstrated ability to do something with the knowledge you have is what is most attractive. The project does not have to be anything large scale.
One way to get practice is to use publicly available data. For example, suppose you were interested in genomic data. You could get a portion (or all, if you have the space) of the 1000 Genomes project, for example. There are a lot of data out there for most bioinformatics tasks. There is often data you can download associated with some research papers.
I hope this helps. Best wishes!
I think the answers given previously reflect my experiences. Please allow me to add a few notes from my own time in bioinformatics.
In academia, usually the focus is on bioinformatics for research in the service of things like determining new molecular biological mechanisms, diagnosing rare genetic diseases in patients, and analyzing and working with new methods (such as new sequencers). Some places you can have careers are university departments (biology, computer science, or bioinformatics), hospitals (particularly check the molecular biology departments), and specialized institutions like the Broad Institute of MIT and Harvard, the National Institute of Health, and the Wellcome Trust Sanger Institute (in the United Kingdom).
In industry, usually the focus is on things like developing a platform (including genetic testing such as for personalized medicine), providing a bioinformatics or some specific in-house analysis as a service, or in development of drugs. (I am familiar with the latter.) Some places you have careers are pharma companies (Merck, Pfizer, etc.), start-ups, and other companies with interest in biology (like Google/Verily and IBM). Just as an aside: there are a host of things regarding start-ups. Make sure to ask questions (either here or elsewhere) regarding them closer to the time you are considering them.
Some places to look for industry bioinformatics job descriptions (just so you know what they look like) are sites like indeed.com, LinkedIn, and Glassdoor. Just search for bioinformatics. For academia, it's a little trickier because sometimes they don't advertise too widely. There are sites like www.bioinformatics.org, www.iscb.org/iscb-careers-job-database, and jobs.newscientist.com/jobs/bioinformatics. In both academia and industry cases, you should also look at the career section of institutions or companies you are interested in.
One of the rarer skills I've seen in bioinformatics is the ability to code quickly and well. If one understands molecular biology and is also a very strong programmer, that is a great asset. The major programming languages in bioinformatics may be Python and Java. It is helpful to know C++ (my primary language), Perl, and bash shell script, but once you know a programming language or two, picking up another one isn't too bad, since the concepts are the same. If one is very strong in both molecular biology and computer science, there are many opportunities.
Knowing something about databases like Oracle and SQL is very useful. You can download for free Oracle 11g Express Edition from their website for development purposes. There are a lot of documentation on Oracle's site as well as elsewhere on the web. Oracle is the dominant database used in pharma (certainly all of the top 10 use it). It is useful in academia too; though due to cost, they may go with MySQL or PostgreSQL. This way, one can organize and query data in a nice structured way. Part of one's job may be to organize a huge amount of information in a way that people can get at it easily. Databases are a prime candidate for such tasks, particularly if they have a nice web interface to them, like Oracle's Application Express.
The other bit that will be of use is knowing a decent amount of statistics. It is used all the time in bioinformatics. One should not limited to just the "usual statistics", but also check out some of the things ecologists use, for example. The very same ideas are used in analyzing microbiome samples. (This was my former job.)
Reflecting on Roshan Shah's response, while it is difficult to predict where things are going in bioinformatics, it can also very much affect what one may want to focus on. For example, suppose one is interested in genomic assembly programs. (These are programs to take little snippets of DNA sequences and assemble it into a one long sequence of DNA.) If and when nanopore sequencing technology comes of age, most knowledge regarding assembly programs will be outdated. This is because one of the main advantages of nanopore sequencing technology is to read long sequences of DNA rather than a short snippet, thus hardly needing assembly. However, the ideas behind genome assembly are fundamental to bioinformatics, so the thinking behind them would still be very applicable elsewhere, even with the advent of nanopore sequencing. Similarly, if one see personalized medicine as the future, then it behooves one to study clinical genomics.
I think the most important skill is analytical reasoning, which is so critical when analyzing biological data. Sometimes programs have bugs. (I have caught problems in other people's widely used code. This is part of the job.) Sometimes the experiments are carried out sub-optimally; not from lack of trying but sometimes reagents go bad, etc. Sometimes the data is very noisy. Working with and fixing such bumps in the road is part and parcel of bioinformatics. Being able to extract maximal understandable results from data without stating something that is statistically unjustified is very valuable.
In closing, I find bioinformatics a total blast! If you are interested in the intersection of computing and biology, it can really place you at the bleeding edge of biology. I hope these notes are helpful. Best of luck!