Bioinformatics Sequence: How To Become Bioinformatics Scientist

A bioinformatics scientist is a professional who applies computational and analytical methods to biological data in order to extract meaningful insights and solve complex biological problems.

Bioinformatics is being used for an array of important tasks like analysis of gene variation & expression, simulation environments, analysis and prediction of gene & protein structure/function, prediction of gene regulation networks, etc. Sequencing is the process of determining the order of nucleotides of DNA molecules. It is performed to determine the order of four bases adenine - adenine (A), guanine (G), cytosine (C), and thymine (T) in a DNA strand.

What is Bioinformatics?

To capture, manage, and interpret large biological data securely has always been a critical task for professionals; here Bioinformatics emerges as a great help by providing data-driven insights that enable professionals across Microbial Genomes to identify genes & proteins, determine their behavior & functionality, define evolutionary relationships, and predict conformation. Bioinformatics extracts knowledge from a large and complex biological data set by developing custom-to-need algorithms and software. According to the NCBI, “Bioinformatics is a set of practices applied through computation technology for collection, analysis, classification, recovery, storage, manipulation, and visualization of biological information.

What Is Bioinformatics Sequence?

Sequence analysis comprehensively represents a data-driven computational analysis of an RNA, DNA, or peptide sequence serving the purpose of extracting information about its biological function, properties, evolution, and structure. One of the significant applications of bioinformatics, Sequence analysis is widely used for the objective-oriented analysis of any organism's protein sequence or nucleotide. Different experimental methods are used to determine a biological sequence.

Types of Bioinformatics Sequencing

Next-generation sequencing differs from how the DNA or RNA samples were prepared and the data was analyzed. There are four types of commonly used Bioinformatics sequencing-

1. DNA Sequencing: It is performed to analyze the entire genome focused on regions of key interest for whole and targeted sequencing or to study DNA-protein interactions.

2. RNA Sequencing: It is performed by using different techniques to serve the purpose of targeted RNA sequencing to single-cell sequencing and to whole-transcriptome sequencing.

3. Methylation Sequencing: It is performed with targeted approaches for genome-wide analysis to have insights into methylation patterns of a single nucleotide level.

4. High-Throughput Sequencing: It is performed by using data-rich applications to process more samples with the purpose to increase statistical power.  

What is Sequence Alignment?

Sequence alignment is a method of arranging sequences of protein, DNA, or RNA to identify similarities present because of functional, evolutionary, and structural relationships between different sequences. The purpose of sequence alignment is the identification of the location of insertions and deletions that may be present in either of the two lineages after the divergence from the common ancestor.

Types of Sequence Alignment

Based on the numbers of comparing sequencing strands, Bioinformatics sequence alignment s of two types:
Pair-wise sequence Alignment: It compares two sequences simultaneously. This alignment is a series of paired bases chosen one base from each sequence. There are three types of pairs:-
(1) matches (the same nucleotide appears in both sequences)

(2) mismatches (different nucleotides found in two sequences)

 (3) gaps (A null base in one sequence and a base in other sequences)

Multiple Sequence Alignment: It is an alignment of three or more sequences of similar size. It is performed to identify common patterns and evolutionary relationships between genes. The key purpose of MSA is detecting structural and functional similarities between proteins with a comparative view to other protein sequences. The heuristic and dynamic approaches are used in most MSA sequence alignments.

Applications of Bioinformatics

Bioinformatics is aimed to enhance the understanding of complex biological processes. Bioinformatics is used to examine proteomics, genomics, 3D structure modeling of proteins, drug designing, image analysis, and more. Bioinformatics plays a key role in the fields of precision and preventive medicines development used to prevent, control, and treat infectious dreadful diseases. The seven more common applications of Bioinformatics are in the fields of-

  • Gene therapy

  • Evolutionary studies

  • Microbial applications

  • Prediction of protein structure

  • Storage and retrieval of data

  • Discovery of new drugs

  • Biometrical analysis for crop management and pest control

Importance of Bioinformatics Sequencing

The challenge: ‘The lack of reproducibility of scientific findings is a great issue to be resolved because it poses a threat to the trustworthiness of outcomes of research. Many important research outputs are not made published in journals.’

Bioinformatics allows existing datasets to be modified and reused. An unprecedented biological data has been created by us. The increasing demand for analysis and interpretation of this data is managed by bioinformatics sequencing. Bioinformatics harnesses the power of mathematics, physics, computer science, and biology. Bioinformatics makes data management in modern biology and medicine objective-oriented. Analysis of genome sequence data is one of the major achievements of bioinformatics. Bioinformatics sequencing provides a functional understanding of the human genome leading scientists and other professionals to accelerate the discovery of drug targets and individualized therapy. With advancing computational power, bioinformatics is continuously improving our ability to discover new antibiotics or make agriculture more sustainable.


The increasing genomic progress needs new tools for information extraction from the available data and sharing the extracted insights within the research community. Collaboration plays an important role in advancing the usage scope of genomics. Bioinformatics toolbox provides a range of algorithms and apps for microarray analysis, Next Generation Sequencing (NGS), gene ontology, and mass spectrometry. The top 10 popular Bioinformatics sequencing tools are-

  • geWorkbench (Hierarchical clustering)
  • BioPerl (Computational molecular biology)
  • Biojava (Ensemble databases)
  • Biopython (Sequence analysis in bioinformatics)
  • UGENE for Linux (Dot plot & Chromatogram visualizations)
  • InterMine (Integrating biological data sources
  • IGV (Interactive genomics viewing)
  • GROMACS (Parameter files and topologies)
  • BLAST (Finding a match between protein & nucleotide sequences)
  • Bedtool (Computing histograms)

A career in Bioinformatics Sequencing

The fast-evolving career prospects for certified bioinformatics sequencing experts are widely spread across many domains like hospitals, pharmaceutical companies, healthcare agencies, data science labs, research & development labs, and biotechnology businesses, drug designing & development, bio-analytics, clinical research, pharmacogenomics, proteomics, etc. The top recruiters of Bioinformatics engineers for different job roles are QIAGEN, GVK Biosciences, Eurofins Scientific, PerkinElmer, Strand Life Sciences, Dassault Systems, Roche, Wipro, Innoplexus, TCS, Silicon Genetics, Tessella, IBM Life Sciences, Ranbaxy, Reliance, Torrent Pharmaceuticals, etc.

Demand for Bioinformatics Scientists is increasing fast. Job growth in Bioinformatics is projected to grow at a rate of 31% up to 2029. The top job titles for Bioinformatics Scientists are Embryologist, Osteologist, Biologist, Bryologist, Paleobotanist, Plant Etiologist, Phytopathologist, etc. At the initial stage, a certified Bioinformatics expert succeeds to get an annual salary of around Rs. 4 lakhs.

Job Roles and Responsibilities of Bioinformatics Engineer/Scientists

Bioinformatics specialists/engineers/scientists are enrolled for a range of job roles and responsibilities like-

  • Analyzing sequencing data
  • Developing software and databases for the particular bioinformatics research
  • Developing mathematical modeling of particular biological processes
  • Auditing and evaluating the quality of the available data
  • Innovating new ways to make analysis faster and objective-oriented
  • Providing technical support for bioinformatics applications
  • Applying statistical methods to analyze large datasets
  • Developing applications for custom-to-need data management and analysis

The Roadmap to Become a Bioinformatics Specialist

Entry-level opportunities are available for those having degrees in computer programming, biology, and bioinformatics. Bioinformatics graduate programs include coursework in statistics, math, biology, chemistry, molecular modeling, molecular cell biology, database management, biochemistry, algorithms, Web development, computer programming, etc. The popular online short-term Bioinformatics certification courses are-

  • Python for Bioinformatics
  • Bacterial Bioinformatics
  • Whole genome sequencing tools and applications
  • Gene expression analysis
  • Molecular diagnostics
  • Bioinformatics Tools & Techniques
  • Dissertation training on Clinical research

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