Computational Biology vs. Bioinformatics

This article seeks to compare and contrast the two fields of computational biology and bioinformatics. As you read along, you should be able to learn all there is to know.

Computational biology and bioinformatics are both multidisciplinary fields with different areas of focus.

While computational biology combines statistics, computer science, and mathematics to solve problems in biology, bioinformatics combines biological knowledge with computer programming and large sets of big data.

Figuring out the differences between the two largely depends on the level of understanding you have about each.

Bioinformatics and Computational Biology

To start our discussion, we first need to explain each of these multidisciplinary fields comprehensively.

These look at the basic definitions and scope, amongst other things.

i. What is Computational Biology?

In its simplest definition, computational biology is the field of active research that involves the study of problems in biology that need statistics or algorithms.

Active professionals in this field are trained in physics, engineering, chemistry, statistics, and biology.

Computational biology can also include the development of theoretical models, algorithms, computational simulations, and mathematical models for statistical inferences.

On the surface, this field may convey the idea of adopting machine learning and other new computing technologies.

It doesn’t include any of those. Regarding its application, computational biology is handy as it can be used instead of lab procedures or in support of it.

The field of precision medicine and preventive medicine is heavily impacted by computational biology.

Here, healthcare techniques are devised or customized for individual patient needs with the adoption of a preventive approach to treatment.

ii. What is Bioinformatics?

As briefly stated, bioinformatics involves computer technology’s application to access stored biological data.

The scope of bioinformatics includes the management & analysis of a comprehensive set of biological data.

Also, research on genetic and microbial diseases relies heavily on bioinformatics. The biomedical field is significantly impacted by bioinformatics through research and development.

Bioinformatics subfields and related disciplines include genetics, genomics, pathway analysis, transcriptomics, and molecular modeling.

Other related fields include phylogenetics, structural analysis, metabolomics, systems biology, metagenomics, and proteomics, amongst others.

Similarities between Computational Biology and Bioinformatics

Starting with similarities, computational biology and bioinformatics are often integrated into laboratories, colleges, and research centers.

Also, both of these are two critical interdisciplinary fields in life sciences.

The fields of computational biology and bioinformatics are interrelated. Also, both occupations use mathematical, computer science, and statistical knowledge to interpret biological research outcomes.

What more? Computational biology and bioinformatics are among new emerging life sciences.

Differences Between Computational Biology and Bioinformatics

To better understand the differences between computational biology and bioinformatics, we’ll need to look at multiple aspects like tools & software, definition, programming & technical knowledge, and subfields.

Other areas to consider include applications, careers, and university academic programs.

i. Tools & Software

Tools used for each of these fields vary.

Popular computational biology tools include Novel miRNA, RNA22 Interactive prediction tools, and RNA22 Precomputed Prediction tools.

More tools include the Batch Submission, mipmap TCGA Expression Profiles, and mipmap: miRNA & isomer mining tool.

Those for bioinformatics include genomic and proteomic browsers and those included in the National Center for Toxicological Research’s List of Tools for Bioinformatics Research.

There are several others we won’t be getting into here.

ii. Definition

To distinguish between computational biology and bioinformatics, we’ll still need to consider their different definitions.

Computational biology is a multidisciplinary field that uses statistics, computer science, and mathematics to solve problems in biology. This is as far as we’ll go with the definition.

Bioinformatics, on the other hand, is another interdisciplinary field. However, it combines computer programming with biological knowledge and big data sets.

It can also be said to be the science of collecting and analyzing complex biological data such as genetic codes.

iii. Programming & Technical Knowledge

Another aspect that highlights the differences between computational biology and bioinformatics is programming and technical knowledge.

Here, computational biology tends to have a limited programming and technical knowledge requirement compared to bioinformatics.

Bioinformatics requires much more programming and technical knowledge than computational biology.

iv. Subfields

There are different subfields under computational biology and bioinformatics. In the case of computational biology, these include computational bioengineering, bioinformatics, and computational biomechanics.

Others include theoretical biology, computational bio-imaging, and mathematical modeling.

For bioinformatics, subfields include computational biology, molecular modeling, genetics, structural analysis, genomics, and metabolomics.

Others include proteomics, phylogenetics, metagenomics, and transcriptomics.

v. Application

In terms of application, computational biology and bioinformatics have unique methods.

For computational biology, applications cover advanced mathematics, stochastic models, radiotherapy, system biology, metabolic pathway studies, and machine learning.

Other applications for computational biology include artificial intelligence, data mining, and cellular biology.

Bioinformatics equally has many applications. Such include molecular medicine, microbial genome application, and artificial intelligence.

Other application areas include antibiotic resistance, personalized medicine, preventive medicine, drug development, and machine learning.

Other applications include gene therapy, evolutionary studies, bio-weapon creation, climate change studies, and forensic analysis.

vi. Careers

Another area of distinction is career responsibilities. By specializing in computational biology, you can fill several career roles, including computational biologist and computer and information research scientist.

Bioinformatics scientist students can hold different professional roles, including data scientist, biostatistician, and bioinformatician.

vii. Academic Programs in Universities

Another way these fields can be distinguished is by comparing university academic programs.

Programs for computational biology include B.SC. in computational biology, M.Sc. in computational biology, and graduate certificates in computational biology.

For bioinformatics, programs include a B.Sc. in bioinformatics and data science, M.Sc. in bioinformatics, and graduate certificates in bioinformatics.

These basic similarities and differences can be easily identified when comparing computational biology with bioinformatics.

Now that you know, you can make informed decisions in choosing your preferred field of study.

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