Is Programming Knowledge Necessary For Career In Bioinformatics?
Biology is the study of living beings, starting from the interaction between species and population to the structural and functional organization of cells and tissues in an individual organism. Biologists collect and interpret huge amounts of data during a study. For example, we have vast volumes of DNA sequence data, but how do we understand which parts of that DNA control the various life processes? How do we determine the function of new proteins that we came across during a study? And how do we predict the structure of a protein, based on the available information of its sequence? Bioinformatics is a tool that helps us to answer these questions.
Bioinformatics can be defined as the application of information technology to study biological processes at the molecular level -ie. digitizing life science. The field of bioinformatics creates a niche for the emergence of a new class of biologists created by computational advancements. It has a collaborative approach that relies on computational methods including mathematical modeling, statistics, programming, simulation studies, analytical methods, etc. to analyze a huge amount of biological data. The objective of bioinformatics is to open new insights about the biological process. It could be about a disease mechanism, yield of new crops or drug therapy.
Bioinformatics has been emerging out to be a critical domain within life sciences, especially under the realm of biotechnology & biomedical sciences. It is not only crucial for the management of biological or genomic data. But, it’s also becoming a key component in the discovery of new diagnostic & therapeutic tools- basic & translational research, clinical practice, and personalized medicine. The field of bioinformatics is multifaceted, applicable to almost all sectors of the life sciences It is very well explored in genomics, proteomics, pharmacovigilance, drug discovery, cheminformatics, and clinical studies. In Omics research, it is crucial to handle and interpret large-scale data. Additionally, bioinformatics also implies a key role in the other branches of life sciences such as agro-science, forensic science, veterinary science, bioenergy, and environmental biotechnology. Thus, bioinformaticians are in high demand in Industry, Research, and Academia.
Currently, bioinformatics is not just a tool for promoting scientific inventions in biotechnology and life sciences research. But, the subject has evolved from its supporting role to its own research arena. Yes, bioinformatics has achieved a buzzword position in life science. Hence, the biomedical science domain is witnessing an outburst of career opportunities in the field of bioinformatics. The call for talented & expertise professionals at the crossways of biology, statistics, and data science is very high.
The requirements by a bioinformatician continue to evolve. There are two paths to shape a career in bioinformatics, both of which require learning a new language. Computer professionals must become eloquent in the language of genomics, genetics, and molecular biology, whereas biologists must grasp skills in data analysis, including statistics, logic, and programming. When picking the perfect career match, many recent graduates seem to forget about the involvement of computer science in bioinformatics. This article is a bird’s eye view to introduce the core programming requirements to frame a career in bioinformatics.
Why does bioinformatics need computation and programming Knowledge?
It is a point of intersection between information technology and biology. The grand goal of bioinformatics is to define predictive methods that permit scientists to model the function and phenotype based on the genome sequence of an organism. Compiling genomic and biochemical data into quantitative and predictive representations of biochemistry and physiology will be the result of the enormous effort of computational biologists.
Some biologists may have an opinion that a good background in organic chemistry, biochemistry and deep knowledge in molecular cell biology is enough to study bioinformatics. But, this may not be true for stepping into a career in an interdisciplinary field like bioinformatics. There must be several entry points and one of them is using the programming language. Programming skills are becoming a requirement across many planes of biology and medicine.
With respect to the diversity and complex nature of problems addressed in biology, and medicine, it is authoritative to be able to tackle each problem with a comprehensive knowledge of available computational tools—so that the right tools can be applied for the problem at hand. The basic and versatile tools in your technology toolbox are programming languages.
The modern programming languages can attain numerous computational achievements, while some are more apt for specific tasks when compared to others. For example, the R language is almost unbeatable in its statistical computing capabilities, whereas the Lisp language is well versed for problems in artificial intelligence, and Erlang shines in fault-tolerant and distributed systems. To become an effective use of a programming language, it is important to not only gain basic proficiency in diverse languages but also to manage the time and energy to master at least a single language.
The knowledge of computing and programming is crucial in computational biology in the aspect of computational modeling and simulation in molecular engineering. This involves making prototypes or models that can be simulated to perceive how they will act before they are installed into real-life applications. Moreover, knowledge in computational programming is essential for the development of new tools which can further open insights in finding solutions to numerous health ailments.
However, this does not imply that one can avoid the fundamental knowledge in cell and molecular biology.
So, let us now discuss the various aspects of a successful launch in the field of bioinformatics – Required educational background
The field of Bioinformatics is very vast, and you can step into this domain taking multiple routes. To start with let us understand the required educational background
– At the +2 level, the perfect grouping would be Chemistry, Physics, Math & Biology or Chemistry, Physics, Biology & Computer Science.
– At the undergraduate level, you could pursue Biotechnology, Biomedical Science, Genetics, Computer Science, Biology, Biochemistry, Molecular biology, Statistics, or Chemical Engineering.
– At the postgraduate level, you would need specialization in Bioinformatics, Computational Biology, Epidemiology, Biostatistics, or Applied Statistics. Since strong computer programming skills are a must to get established as a bioinformatics engineer, earning a Master of Science (M.S.) in Computer Science is also a popular option.
Going ahead, the core requirements to become a bioinformatician fall under different domains.
1.Required computational Skills: Knowledge in Software & Programming:
C, C++, Java, R, MATLAB, Perl, Bash, Python, Galaxy. Linux and UNIX sysadmin skills are kind of mandatory. Knowledge of UNIX is enormously beneficial in bioinformatics. You should be also familiar with Machine learning tools and libraries such as Mllib and Scikit-Learn in python
- Sequence alignment tools such as Blast or Bowtie
- The Genome Analysis Toolkit (GATK)
- Software for Next Generation Sequencing, Microarray, qPCR, and Data Analysis (Partek)
- Tools for handling high throughput sequencing data like (samtools)
- To get gene data sets use a tool such as (Ensemble)
- Tools for database search systems like (Entrez)
- T-coffee sequence analysis algorithms and clustering tools
3.Bioinformatics Resources and Database Skills
UCSC genome browser, NCBI, Entrez, SRS Database, UniProt, SwissProt, MySQL
4.Sub-domain software (toolkits):
- Proteomics: Scaffold, ProtMAX,
- Cheminformatics: ChemmineR, Enalos, Indigo, PerlMol, OEChem,
- Molecular Docking & Drug Discovery: Oracle Argus, ARISg, AutoDock, SwissDock, etc.
6.Data Mining: being able to extract data from diverse resources. Getting Familiarised with techniques like hierarchical clustering and decision trees is also useful
7.Data Visualization: extract complex data and interpret it into models and effectively communicate with biologists
8.Genomic and Genetic Knowledge – This forms the core of bioinformatics. Some of the highly demanded skills are high-throughput sequencing, computational genomics, and next-generation sequencing.
When choosing the perfect career match, studying bioinformatics is a promising bet to professional success. Bioinformaticians enjoy an array of research and professional jobs and get competitive salaries. Bioinformatics expertise is invaluable. Ground-breaking technological abilities and productivity are intrinsic qualities of bioinformaticians, widening their employability in the modern scientific community undergoing long lasting renewal
But, before you choose a career in this field, you should be clear enough about the sectors and applications of Bioinformatics which interest you. For gaining a better understanding of what the field entails read scientific journals in these areas so that you can make informed decisions about your future. In fact, it is not an easy task to get into bioinformatics programs acquainted in only biology, or computer science. Instead, you have to demonstrate you know more than a little of both as it a blend of life science and computer science.