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An Overview Of Bioinformatics And Data Science

The field of data science might have found its popularity in recent years when technological advancements were at their peak. However, the origins of this discipline date back to the 1960s. Modern data science is the combined result of several other disciplines such as mathematics, statistics, computer science, and machine learning. Therefore, you can understand the years of evolution it had to undergo to reach the state it is today. Over the years, data science has combined contemporary technologies like artificial intelligence to automate different sectors and provide data scientists with a wider scope such as combining bioinformatics and data science.

An overview of bioinformatics and data science

How Can I Define Data Science?

Data science is a subject that works towards extracting meaningful insights from raw data to help businesses. It combines several interdisciplinary practices to obtain the best results when analyzing large amounts of data.

There is an entire data science life cycle that you can learn about as a student, including data collection procedures. This generally involves customer surveys or product reviews by the customers.

Another aspect that is essential to understand is the concept of ‘big data’. You might come across first-hand or second-hand data sources and these are typically huge in quantity.

In data science this is quite a common phenomenon, so huge quantities of data get to be referred to as ‘big data’. While you get involved in the subject, you will come across several industry-relevant tools designed to help you with the effective handling of big data.

In the 21st century, data science is a growing career path that provides opportunities for data scientists to venture into different fields. Thus in the future, there might be more opportunities for bioinformatics and data science careers.

How Can I Define Bioinformatics?

Just like data science, bioinformatics is an interdisciplinary field where computer science and biology combine with the intent to acquire, store, analyze, and disseminate biological data. It is specialized in handling large and complex data, which is seen in both subjects.

Its processes involve several tools and software to filter large quantities of data and extract insights that are meaningful to specific requests. Mathematical formulas and statistics also have to play a part when evaluating the relationships of large quantities of datasets.

On the other hand, image and signal processing is used to extract valuable results from huge amounts of raw data. The field of bioinformatics is especially valuable in genomics, where computer science can be utilized to identify genes and nucleotide polymorphisms.

They can also be useful in detecting and understanding the genetic basis of disease, distinction within a population, and unique adaptations.

This field was brought to existence by Margaret Dayhoff with the combined applications of mathematics and computer science. Even if both the subjects seem similar in the use of disciplines, they are indeed distinct.

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What Are the Benefits of Studying Bioinformatics and Data Science?

You might have questioned the possibility of how well these industries work. Or what can you possibly gain from a degree in both? It is quite common to think about it before you enroll in a course.

Since, the advent of Artificial Intelligence and its increasing popularity, many have had the fear of manual jobs losing their potential. However, these two job markets make good use of the AI technologies that provide them with a competitive edge.

So, if you’re still thinking about pursuing either of the fields, the following list might give you a boost:

Opportunities in the Job Market – In terms of scope, these two fields have plenty to give you. Data science is one industry that has a plethora of jobs and industries lined up for you.

Even if you are a beginner in the field or an experienced professional who’s switching careers or looking for networks, your opportunities will not be compromised. Bioinformatics also does not fall too far from bringing you career growth potential.

The easiest way to start your journey is to take up a professional course on your ideal choice of subject because a professional degree holds great value to your profile and leaves a good impression on your employers.

These professional courses are equipped with case studies, projects, and mentorship sessions which help you get the right amount of practical exposure in the industry.

Informed and Improved Decisions – what you are studying can significantly shape your judgment and this is true when you’re thinking of pursuing either of the two career paths.

Something common in both bioinformatics and data science is the availability of data because data is what forms the base of the subject. In the case of data science, data can be collected from the surveys conducted by businesses aimed at their target customers so that the business can understand its customer base better.

Raw data is also collected by the weather department, which is later transformed into meaningful information with data science, enabling us to understand weather reports.

So, with better guidance, you could improve your decision-making abilities because in these fields you cannot afford to let your non-technical background affect you.

Well-structured and Organized– the biggest benefit of professional or curated courses is the organized guidance you can get. You can always enhance your knowledge about a particular topic without enrolling in a course, but that sometimes costs you uncategorized information or incorrect knowledge.

You would want some degree of serialization of the topics you learn about, especially if you’re starting your learning journey.

Professional courses designed for beginners can be an answer to your problems because not only will these courses update your knowledge with the right resources, but also enhance your experience with interactive sessions, personalized mentoring, skill-based training, and internship opportunities.

Hand-held Guidance – it is a given for professional curated courses to come with specialized hand-held guidance from industry experts. It is exclusive to everyone who is partaking in these special classes held by the institution.

Both of these career paths require well-trained professionals to fill the gap in the job market and there is no better way for it than learning directly from experts.

Students of these professional courses can gain guidance in their formative years of career growth and get their money’s worth when they land a high-end job. Sometimes, institutes have placement assistance cells to help their students get placed with renowned companies.

Getting Your Facts Right – Unlike other sources of information on the internet, there is no better way to get trained than through official learning platforms.

You might uncover something, like a personal experience or exclusive facts, which is not available in general. Bioinformatics courses can help you better understand the procedure of drug simulation and predicting the virulence of new pathogens.

Moreover, it can enhance your decisions related to algorithm design, evaluating heart function, and predicting post-operative complications. Professional bioinformatics courses train you on the ways of creating treatment plans that are specific to the patient’s unique genetic material.

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What Are the Prominent Differences Between Bioinformatics and Data Science?

At first glance, both might seem to be something from a similar domain. It applies similar processes and even technologies to get its results, but the differences between the two come to light only when you dive deeper into the two subjects.

The field of data science presents you with a much broader scope and a plethora of opportunities to grab in the year 2024. Data science jobs are abundant in the market and qualified individuals can find a clear trajectory for their personal and career growth.

As previously mentioned, the advancements in technology have granted data scientists the power to uncover hidden or complex patterns and trends within raw data.

This helps the data science industry grow, aids businesses invest in specific data-driven strategies to gain a competitive edge amidst other career paths, and improves the quality of results obtained by modern data scientists.

On the other hand, bioinformatics proves to be an equally lucrative field that is loaded with opportunities for aspirants who want to make it big.

Bioinformatics and data science equally combine multiple fields, but in the case of the former, the subjects involved are biology, computer science, mathematics, engineering, and statistics for analyzing biological data.

Moreover, the field of bioinformatics has been around for a longer period before data science reached its peak popularity among curious minds.

Amidst data science jobs in the year 2024, the scope for bioinformatics is bright because, unlike data science, the field focuses on analyzing biological data and other scientific aspects.

There is immense potential in the professional courses on the subject and under proper guidance you could excel in the field in no time.

In terms of skills, both bioinformatics and data science can be differentiated in certain ways. But something that you need to ingrain is the ability to learn and work with complex technologies.

Bioinformaticians used their skills to effectively sequence tools such as Blast or Bowtie, learn to work with the Genome Analysis Toolkit known as GATK and handle software for next-gen sequencing or microarray.

They are trained to handle high-throughput sequencing data like Samtools and can work with ensemble techniques used to gather gene data sets. Sometimes skill-based tools like Entrez can help bioinformatics database search systems.

Data science is well equipped for all sorts of data and data scientists are required to have the basic computation, mathematics, and statistical skills to process. The main goal here is to apply your knowledge of high-end tools and software to understand what the results signify.

Both are distinctly different in terms of the purpose they serve. In the case of data science, you would have to perform routine experiments and extract information from them.

These results can serve a wider purpose such as benefit the organization you are working for or be used for the smooth functioning of society in general. When working for a business or organization, your focus should be on how the data affects the business’s products and consumers.

Understanding it will guide your decision on the right track and improve the business’s standing among customers. While bioinformatics focuses more on the academic research aspects along with the medical fields.

It is a part of biology which is why its approach to consumer effects isn’t very strong. Another aspect that differentiates between both fields is the supply and demand of candidates.

Both these fields apply separate work cultures to operate efficiently. However, data science jobs are open to a wider range of applicants who fit the general criteria and have the relevant skills.

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You can enroll in a data science professional course without having any prior knowledge or background in the data science field. Jobs in bioinformatics are usually not very lenient with their selection of candidates and their supply of skilled professionals is limited.

Individuals who seek to pursue the data science field can find work in several industries other than Information technology. Some industries that provide ample opportunities for a data scientist to grow are transportation, retail, management, marketing, medical, healthcare, business, and finance.

On the other hand, bioinformatics concerns the medical line and provides opportunities in research, bioinformatics development, bioinformatics data science, computational biology, microbiology, zoology, biostatistics, and medical coding.

What Are the Different Types of Bioinformatics Databases?

Bioinformatics databases or biological databases consist of complex biological data that can be compared to protein sequencing, molecular, structure, DNA sequences, etc. These are generally archives that provide some insight into annotations, pathways, and disease information.

The nature of biological data is vast, exception-ridden, and incomplete so the bioinformatics databases are created and optimized to ensure clear results.

When such biological data is transferred to the computer in a readable way, it enhances the speed of research and helps you retrieve information without hindrance.

It must also be kept up-to-date quite frequently. Now, when it comes to the types of bioinformatics databases, you get to learn about 3 areas – primary, secondary, and specialized databases.

1. Primary Databases – The first type among bioinformatics databases is the primary database which holds information in sequence or structure.

There are results submitted by the scientists which are archived into the databases, mostly populated with experimentally derived data such as genome sequence and macromolecular structure.

Moreover, these databases typically remain uncurated raw data, and generally, no modifications are performed over the data.

Unlike other types, you will be able to find biological data that is unique and which is made available straight from the laboratory.

The data is also numbered when entered into databases, which makes it easier to recognize when the same data is being retrieved using the accession numbers. These accession numbers are permanent, making the raw data differentiable.

Some examples of this primary database include Nucleic acid databases (GenBank) and Protein databases (PDB).

2. Secondary Databases – In the second type of bioinformatics database, you can find the results of the previously uncurated data which has been processed and stored using computational or manual methods.

Most of the time, computational algorithms are applied to the primary databases so that valuable and informative data can be stored in the secondary databases.

These databases are heavily curated which is processing the data before it is presented. This makes the database better and helps you seek information that is more useful compared to your previous findings.

Some examples of this database include InterPro (mostly used in the case of protein families, motifs, and domains) and UniProt Knowledgebase (which is utilized in the case of sequence and functional information on proteins).

3. Specialized Databases – Lastly in the types of bioinformatics databases, you get data that is compared before it is entered into the database and later filtered as per the need or criteria.

The specialized databases generally serve a specific research interest. These are created with a specific topic in mind, such as a specific organism or type of data. Some important examples of specialized databases are PubMed, Embase, Scopus, CINAHL, and Micromedex.

What Purpose Do These Databases Serve?

As you can already tell from previous topics, sub-components of both subjects have a purpose to play in their respective fields. From the following list, you will get an idea about the possible purposes served by biological databases:

  • These databases provide opportunities for organizations to seek a wider number of biological data in structured ways.
  • The biological databases also act as important resources for scientific researchers or individuals researching in this field, to look for information that helps them progress.
  • The biological databases can be utilized for developing new bioinformatics tools and methods so that research can be taken forward.

These databases also enable a collaboration aspect between different researchers and facilitate the process of sharing resources and data.

What is the Importance of Bioinformatics as a Career?

Bioinformatics and data science are two fields that play a massive role in modern society. Data is spread all around us and without trained professionals like data scientists or bioinformaticians we would have been lost.

Thus, it is important to understand why we need it. Bioinformatics is specially focused on the scientific aspects, using biology, chemistry, physics, and computer science to form a judgment.

Below are some of the points you should be aware of when pursuing a career in bioinformatics:

Drug Development – medicine or common drug development requires some expert-level knowledge and experience. The process involves the identification of medicines, framing new approaches for controlling diseases, optimization, and a few other steps.

With bioinformatics, you can understand the disease symptoms of genetic mutation and access the impact of environmental health as well as the potential of rug resistance.

Research in this line simulates drug interactions and helps repurpose the existing compounds. It facilitates the cure for treating diseases like cancer, diabetes, cardiovascular and neurodegenerative diseases.

Bioinformatics can also aid molecular data in forming comparisons between patients, animal disease models, cancer cells, and normal controls

Evolutionary Biology – this concept helps you understand the astonishing diversity that exists in this world. It arises by integrating insights from genomes, development biology, natural population studies, and experimental analyses.

When this is combined with bioinformatics, you can get a tool for efficiently analyzing and interpreting large data sets of biological data, so that you can better explain the role of evolution in the development of life. In short, the discipline helps scientists study the genetic code of organisms.

Pathogen Prediction – another role fulfilled by this discipline is pathogen prediction, by helping researchers link different data from genes to the movement of fats, proteins, and metabolites in cells.

This could help predict the virulence of new pathogens. The process requires you to get a detailed understanding of various attributes in both the pathogen and its host. The types of pathogens could include bacteria strains, fungi, viruses, parasites, and more.

Human Microbiomes – the application of bioinformatics in this aspect helps researchers to uncover new clues related to health, from human microbiomes. In scientific terms, the human microbiome represents a diverse community of microbes, each serving an important role in the maintenance of the human body.

The modern technologies that have contributed to sequencing and computational methods have boosted microbiome analysis for better resolution. In the present scenario, this field of research has given rise to massive data sets and contributed to the development of analysis tools.

FAQs

Q.1) What is the Average Salary for Data Science or Bioinformatics?

The average salary for anybody working in the field of bioinformatics is 6 Lakhs, while data scientists can earn an average pay of 14.5 Lakhs.

Q.2) Can I Work in Bioinformatics With Data Science?

Yes, if you’re thinking of switching careers or starting in the field of bioinformatics. The fields are somewhat similar in their approach to solving a problem, although, certain aspects like tools and skill sets can differ.

Q.3) Is Bioinformatics Better Than Data Science?

Both fields have equal growth potential, however, the gap in supply and demand between the two disciplines can cause a problem. Bioinformatics focuses solely on the scientific aspects while data science is a generic field of study. Therefore, the availability of data science jobs may be more than the former.

Conclusion

So, we can conclude by saying that these two disciplines can have you covered for a long time. If you are seeking a lucrative career path within the data industry, you can prosper with either of these. However, bioinformatics has been a topic of study for a longer time and might be the subject that gave rise to the broader and more generic subject called data science. Both fields have immense popularity and career growth potential as per today’s standards.

I am Meghna Kanjilal, an Education honours graduate from Loreto College with a passion for reading books. I like being creative whether it's through writing or designing. I had an amazing opportunity to start my writing journey with IIM Skills and expand my knowledge in the Content Writing domain. Currently, I am working with IIM skills on their internship programme to enhance my skills and gain experience.

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