MCQs on Bioinformatics

Bioinformatics is an interdisciplinary field, developing software tools and methods for understanding biological data in detail when the data sets are complex and broad. As an interdisciplinary science field, bioinformatics combines biology with computer science, mathematics, information engineering, and also statistics to analyze, interpret biological data. Bioinformatics has been used in silico analyses of biological queries using statistical and mathematical techniques.

In addition, bioinformatics also includes the biological studies that use computer programming as their methodology part, and as specific analysis, "pipelines" are repeatedly used especially in the field of genomics. Bioinformatics' common uses are the identification of candidates, genes, and Single Nucleotide Polymorphisms (SNPs). Such kind of identification is often made for a better understanding of the genetic basis of unique adaptations, disease, the differences between populations, or the desirable properties (especially in agricultural species). Less formally, bioinformatics also tries to understand the organizational principles within protein sequences and nucleic acid, known as proteomics.

The bioinformatics questions based on the bioinformatics MCQ book will help students crack the NEET in a better way.

Let us Look at Some of the MCQs on Bioinformatics.

1. Which of the Following Statements is Incorrect about the RNA Secondary Structure’s Prediction?

1. Every base is compared first to every other base by a type of analysis quite similar to that of dot matrix analysis

2. A matches row in the RNA matrix indicates a complementary nucleotides succession that can potentially produce a double-stranded region

3. The sequence is listed across the side of the page, top and down, G/C, G/U, and A/U base pairs are scored

4. A row of matches in the RNA matrix represents a failure of complementary nucleotides that can potentially produce a double-stranded region

Answer: (d)

Explanation

The energy of each structure, which is predicted, is estimated by the nearest-neighbour rule by summing the negative base-stacking energies for each base pair in the double-stranded regions. By adding the estimated positive energies of destabilizing regions like loops at the hairpin end, internal bulges, bulges within hairpins, and other unpaired regions.

2. Identify the following statement, either True or False?

Evaluation of all the different possible configurations is done through a single scoring matrix.

1. False

2. True

Answer: (a)

Explanation

To find the most energetically favourable, and to evaluate all the different possible configurations, different types of scoring matrices are used. The complementary regions are then evaluated by a dynamic programming algorithm to predict the most energetically stable molecule. The method is similar compared to the dynamic programming method that is used for sequence alignment.

3. Which Regions in Sequences, Similar to those in RNA that will Form the Secondary Structures, are the Examples of Such Kinds of Context-Free Sequences.

1. Non-Complementary

2. Complementary

3. Non-interlocking

4. Non-compatible

Answer: (c)

Explanation

Stochastic Context-Free Grammars (SCFG) introduce into the definition of such regions’ uncertainty. It also allows them to use alternative symbols, as found in the evolution of RNA molecules.

4. Identify the Following Statement, either True or False?

The SCFGs application to RNA secondary structure analysis is so similar in form to the probabilistic covariance models. Is this statement True or False?

a) False

b) True

Answer: (b)

Explanation

The alphabet symbols for RNA are A, C, G, and U. The Context-Free Grammar establishes a set of rules that are known as productions for generating the sequence from the alphabet, and in this case, an RNA molecule with sections that can base-pair and others that cannot base-pair.

5. Identify the Following Statement, either True or False?

The SCFGs that are used in the production analysis of RNA secondary structure are very similar compared to that of the covariance model, with the grammatical productions resembling the nodes in the ordered binary tree.

1. False

2. True

Answer: (b)

Explanation

According to the hidden Markov models, the probability distribution of each production must be derived by training with the known sequences. The algorithms used in SCFG training and for the sequence aligning with the SCFG are a bit different from those which are used with Markov models that are hidden, and the memory requirements, time are greater.

6. The Human Genome Approximately Contains ______ Pairs.

1. 3 billion base pairs

2. 5 billion base pairs

3. 6 billion base pairs

4. 4 billion base pairs

Answer: (a)

7. The SWISS PROT Protein Sequence Database has begun in the Year ______?

1. 1988

2. 1987

3. 1986

4. 1988

Answer: (b)

8. Which of These Following are not Bioinformatics Applications?

1. Data storage and management

2. Understand the relationships between organisms

3. Drug designing

4. None of the above

Answer: (d)

9. The Laboratory Work is Done using the Computers and Associated with Web-Based Analysis Online is Generally referred to as __________?

1. Insilico

2. Wet lab

3. Dry lab

4. All of the above

Answer: (b)

10. The Laboratory Work is Done using the Computers and Computer-Generated Models Offline Generally is referred to as _______?

1. Dry lab

2. Wet lab

3. Insilico

4. All of the above

Answer: (a)

11. The Latin Term “Invitro” refers to_______ ?

1. Outside the lab

2. Outside the glass

3. Within the lab

4. Within the glass

Answer: (d)

12. The computational methodology that tries to identify the best matching between two molecules, a ligand and receptor are known as _______?

1. Molecular matching

2. Molecule affinity checking

3. Molecular docking

4. Molecular fitting

Answer: (c)

About Bioinformatics

Bioinformatics is the application of computer science and other quantitative approaches to the study of biological systems. It is a field that is part of molecular biology. Bioinformatics may use various information types to provide data about biological systems and is an essential discipline in the emerging field of functional genomics. Bioinformatics is the application of computers to biological data, such as DNA sequence analysis, structure prediction, and functional annotation. It takes data and information from many sources and applies them to find new trends or relationships within the data. Bioinformatics is an active and growing discipline.

Bioinformatics is applied to the full range of biological and biomedical sciences, including genomics, proteomics, computational biology, bioinformatics, and molecular biology. Bioinformatics is a component of biology and medicine, which includes genomics, proteomics, molecular biology, biochemistry, cell biology and computational biology. Bioinformatics as an individual area of study is a very broad subject and includes fields of computational biology and molecular biology.

The field of bioinformatics has three interrelated objectives:

• understanding the function of DNA and proteins, especially through the process of gene sequencing and structure prediction.

• understanding how to predict the effects of human genes on human health. 

• improving the effectiveness of existing procedures for detecting disease and finding treatment methods.

It involves the application of computer science to provide data about biological systems, such as genetic information, protein sequence analysis, and functional annotation. Bioinformatics has become a rapidly growing field, with over 150,000 articles published annually.

History 

The study of biology dates back to the 19th century. In the 1890s, the first human genome was discovered. The genome consisted of the DNA that was found in a person's chromosomes. 

In 1953, Watson and Crick discovered DNA's double-helix structure. The term bioinformatics was coined by Michael Toman and Tom Land in the 1980s. It comes from biology and informatics, which are both broad fields. Bioinformatics first became popularized as part of genomics.

Bioinformatics has become a big and growing field. Bioinformatics started around 1990 as a result of DNA sequencing, genomics, and molecular biology. More and more information about human genes was being accumulated. In addition, there was more interest in understanding the genes. 

A computational problem was that scientists needed to have tools to organize and analyze data in a biological context. There was also a need for better ways to visualize large amounts of data. It was clear that biologists and computer scientists had to work together to answer some of these problems. 

The main problems that led to the development of bioinformatics are "understanding the function of DNA and proteins, especially through the process of gene sequencing and structure prediction. Understanding how to predict the effects of human genes on human health. Improving the computer software tools and techniques used to carry out genomics research. "

There are different types of bioinformatics. "There are biological studies done in bioinformatics, computational studies done in bioinformatics, and tools for performing some aspects of bioinformatics. 

Bioinformatics is used to describe the research done to understand and study life. Bioinformatics is becoming very interesting. Bioinformatics is used to help find gene defects and mutations. The field is also used to help determine ways to create new pharmaceuticals. New uses for bioinformatics are being found.

There are different types of bioinformatics. The first type of bioinformatics is called genomics. Genomics is the study of an organism's entire genome.

This means studying all the DNA and proteins present in an organism. Genomics is used to understand the effects that the genes of an organism have on its physiology, phenotype, and morphology. There are different types of genomics. 

Genome-wide sequencing is used to sequence the entire genome of an organism, to find any unusual genes. Functional genomics focuses on how genes are involved in a process and how the processes work. Proteomics is used to understand the function of proteins by identifying them and determining what role they play in a process. 

The next category of bioinformatics is epigenomics. Epigenomics is used to study DNA in its environment that aims and not just the DNA sequence. There are different types of epigenomics, including epigenomic profiling, whole-genome methylation, and whole-genome chromatin immunoprecipitation (ChIP) analysis. 

Lastly, there is metabolic genomics. This category is used to understand the functions of enzymes in an organism. Metabolic genomics is used to find the function of every enzyme of an organism.

Types of Bioinformatics

There are different types of bioinformatics, which are:

• Genomics: Genomics is the study of the genome of an organism. Genomics is the study of an organism's entire genome.

• Epigenomics: Epigenomics is the study of how DNA and histones in the cell act together. It helps scientists understand the gene. It provides a better understanding of how genes are regulated and how they work.

• Proteomics: Proteomics is the study of proteins in a cell or organism. Proteins are very important because they have a huge role in almost all processes in an organism. Proteins determine the phenotype of an organism.

• Metabolomics: Metabolomics is used to study the structure and function of metabolites in an organism or cell. It is used to determine what all the compounds are in an organism. It helps in the identification of how metabolites work.

• Structural bioinformatics: This type of bioinformatics is used to determine the structure of the protein.

• Computational genomics: This type of bioinformatics helps to understand the role of all the biological information within the genome. It also helps to find which genes or proteins are active at a given time.

• Functional genomics: This type of bioinformatics is used to understand the function of a protein. It helps to understand how a protein works.

• Computational proteomics: This type of bioinformatics helps to understand the active sites and function of proteins. It helps to determine whether a particular protein is a substrate or an enzyme.

• Metabolic genomics: This type of bioinformatics helps to understand the function of all the enzymes in an organism. It helps to understand the biochemical pathways within an organism.

• Gene discovery: This type of bioinformatics helps to study the genes of the organisms within a very small range. It helps in the development of new drugs and treatments.

• Synthetic biology: This type of bioinformatics helps to understand the functions and structures of DNA molecules and their processes. This helps to understand the way to build new organisms.

• Systems biology: This type of bioinformatics is used to study the function of different genes within the genome. It helps to identify the functions and relationships between different genes.

• Comparative genomics: This type of bioinformatics is used to understand how different genes and their functions interact within the genome of different organisms.