B.Tech. DEGREE EXAMINATION, JULY 2023
21BTB102T - INTRODUCTION TO COMPUTATIONAL BIOLOGY

Detailed Solution:
Step 1: Photosynthesis is the process by which plants and some other organisms use sunlight to synthesize foods from carbon dioxide and water.
Step 2: This process occurs in specialized double-membraned organelles called Chloroplasts, which contain the green pigment chlorophyll that captures light energy.
Step 3: The other options serve different functions: ER (protein/lipid synthesis), Cell wall (structural support), and Ribosomes (protein synthesis).

Detailed Solution:
Step 1: During Prophase I of meiosis, homologous chromosomes (one inherited from the mother, one from the father) pair up.
Step 2: While paired, non-sister chromatids break and exchange equivalent segments of DNA at points called chiasmata.
Step 3: This physical exchange of genetic material between paternal and maternal chromosomes is specifically called Crossing over (or homologous recombination), which increases genetic diversity.

Detailed Solution:
Step 1: A eukaryotic organism has a true, membrane-bound nucleus.
Step 2: Bacteria are prokaryotes. Ferns are multicellular eukaryotes.
Step 3: While Protozoa (D) are also single-celled eukaryotes, Yeast (A) (often misspelled as 'Yeart' in question papers) is the classic biological model organism for a single-celled eukaryotic fungus (e.g., Saccharomyces cerevisiae). (Both A and D are technically correct, but A is the standard specific example expected in this context).

Detailed Solution:
Step 1: Cells require compartments to store water, nutrients, ions, and waste products.
Step 2: Vacuoles are large, membrane-bound, fluid-filled sacs that serve this exact storage function. Plant cells typically have a single large central vacuole that also maintains turgor pressure.

Detailed Solution:
Step 1: Scurvy is caused by Vitamin C deficiency. Rickets by Vitamin D/Calcium deficiency. Sickle cell anemia is a genetic protein (hemoglobin) mutation.
Step 2: Atherosclerosis is a disease characterized by the buildup of cholesterol and lipid plaques on the inner walls of the arteries, causing them to narrow and harden. Thus, it is directly a lipid-related disease.

Detailed Solution:
Step 1: Chemically, a carbohydrate is defined as an organic compound containing carbon, hydrogen, and oxygen.
Step 2: The strict chemical definition of a carbohydrate is a polyhydroxy aldehyde or a polyhydroxy ketone (or substances that yield such compounds upon hydrolysis).
Step 3: They contain multiple hydroxyl (-OH) groups and a carbonyl group (C=O) which is either an aldehyde (on the end carbon) or a ketone (on an inner carbon).

Detailed Solution:
Step 1: DNA is a polymer of nucleotides.
Step 2: The backbone of a DNA strand is formed by linking the 3' carbon of one sugar to the 5' carbon of the next sugar via a phosphate group.
Step 3: This strong covalent linkage is called a phosphodiester bond. (Note: Glycosidic bonds link the sugar to the base, but phosphodiester is the defining polymeric bond of nucleic acids).

Detailed Solution:
Step 1: Lipopolysaccharides (LPS) are large molecules consisting of a lipid and a polysaccharide.
Step 2: They are the major component of the outer membrane of Gram-negative bacteria.
Step 3: Because the outer membrane is a type of lipid bilayer envelope, "Cell membrane" is the most biologically accurate answer among the choices.

Detailed Solution:
Step 1: The standard genetic code contains exactly three stop (termination) codons that signal the end of protein translation.
Step 2: These three codons are UAA (Ochre), UAG (Amber), and UGA (Opal).
Step 3: CGA is a sense codon that codes for the amino acid Arginine, meaning it is NOT a stop codon.

Detailed Solution:
Step 1: Proteins are broadly classified by shape into globular proteins (spherical, soluble) and fibrous proteins (long filaments, insoluble).
Step 2: Globular proteins generally carry out active biological processes (enzymes, transport, metabolism).
Step 3: Fibrous proteins (like collagen, keratin, and elastin) are tough and mechanically strong, making them perfectly suited for structural functions (forming hair, skin, tendons, and cell cytoskeleton).

Detailed Solution:
Step 1: Amyloidosis is a group of diseases in which abnormal proteins build up in tissues as amyloid fibrils.
Step 2: The fundamental molecular event in amyloid formation is a massive conformational change where soluble proteins misfold and adopt a predominant beta-sheet configuration.
Step 3: Beta-sheets are a type of secondary structure. The transformation from normal alpha-helices or random coils into rigid beta-sheets causes the proteins to aggregate into insoluble amyloid plaques.

Detailed Solution:
Step 1: In bioinformatics, a primary database stores raw, experimentally derived data submitted directly by scientists (e.g., raw DNA sequences or raw 3D coordinates). A secondary database stores derived information, patterns, or motifs computed from primary databases.
Step 2: The Protein Data Bank (PDB) archives raw, experimentally determined 3D atomic coordinates of biological macromolecules (from X-ray crystallography, NMR, or cryo-EM).
Step 3: Because it hosts the original experimental data, it is classified as a primary database.

Detailed Solution:
Step 1: A typical neuron has a cell body (soma), a single long projection for sending signals (axon), and multiple short branching projections for receiving signals.
Step 2: These multiple, tree-like branch projections extending from the cell body are called Dendrites.

Detailed Solution:
Step 1: Monocytes are a type of white blood cell that circulate in the blood and migrate into tissues to differentiate into resident macrophages.
Step 2: Astrocytes and Oligodendrocytes are of neuroectodermal origin.
Step 3: Microglia are the specialized, resident macrophages of the central nervous system (brain). They are of mesodermal origin, developmentally related to peripheral monocytes/macrophages.

Detailed Solution:
Step 1: Multiple Sclerosis (MS) is an autoimmune demyelinating disease of the Central Nervous System (CNS).
Step 2: In reality, MS is caused by the destruction of oligodendrocytes, which produce myelin in the CNS. Schwann cells produce myelin in the Peripheral Nervous System (PNS).
Step 3: However, based on the provided options, the question is likely referring generically to the destruction of myelin-producing cells. Since oligodendrocytes are not listed, Schwann cells (A) is intended as the proxy answer for "cells that make myelin," despite the biological inaccuracy regarding CNS vs PNS.

Detailed Solution:
Step 1: Machine learning is broadly categorized into three main paradigms based on how the algorithm is trained.
Step 2: These paradigms are Supervised Learning (trained on labeled data), Unsupervised Learning (trained on unlabelled data), and Reinforcement Learning.
Step 3: Both (B) and (C) are correct primary types of machine learning. In exam contexts, either B or C is considered a valid "type" to select, though the question lacks an "All of the above" option.

Detailed Solution:
Step 1: Upon initial exposure to a pathogen, the adaptive immune system mounts a primary response.
Step 2: While plasma cells secrete active antibodies to fight the current infection, a fraction of activated B and T cells differentiate into long-lived Memory cells.
Step 3: These memory cells circulate in the body for decades, allowing for the rapid and robust "subsequent recognition" and clearance of the same antigen if it ever invades again.

Detailed Solution:
Step 1: The general process of a cell engulfing material is endocytosis. However, engulfing large, solid particles (like bacteria or "prey") has a specific name.
Step 2: This specialized form of endocytosis used by immune cells (macrophages and neutrophils) to physically surround, ingest, and destroy large pathogens is called Phagocytosis (from Greek phagein = to devour).

Detailed Solution:
Step 1: An autoimmune disease occurs when the body's immune system erroneously attacks its own healthy tissues (e.g., Rheumatoid arthritis attacks joints, Multiple sclerosis attacks myelin, Lupus/Lupers attacks systemic tissues).
Step 2: Influenza (the flu) is an infectious disease caused by an external viral pathogen (the influenza virus), not by the body attacking itself.

Detailed Solution:
Step 1: When tissue is injured or encounters an allergen, local immune cells trigger an inflammatory response.
Step 2: Mast cells (resident in connective tissues) heavily degranulate, releasing copious amounts of histamine.
Step 3: Histamine causes local vasodilation and increased capillary permeability, creating chemical gradients that attract other circulating immune cells (like neutrophils) to the site of infection/injury.

1. Introduction to Stem Cells:
Stem cells are unspecialized "master" cells of the body from which all other cells with specialized functions are generated.

2. Fundamental Properties of Stem Cells:

• Self-Renewal: Stem cells can undergo numerous cycles of cell division (mitosis) while maintaining their undifferentiated, unspecialized state indefinitely. This ensures the body always has a reservoir of stem cells.
• Potency (Differentiation): Given the right biochemical signals, stem cells have the capacity to develop (differentiate) into specialized functional cell types (like heart muscle cells, neurons, or red blood cells). This potency is graded:
  • Totipotent: Can form an entire organism (e.g., Zygote).
  • Pluripotent: Can form any tissue in the body but not the placenta (e.g., Embryonic Stem Cells).
  • Multipotent: Can form a limited, related range of cells (e.g., Adult Hematopoietic stem cells making only blood cells).

3. Applications of Stem Cells:

• Tissue Regeneration (Cell Therapy): The most critical application. Stem cells can be coaxed to differentiate into specific cell types to repair or replace damaged/diseased organs. (e.g., replacing damaged neurons in Parkinson's disease, or regenerating pancreatic beta cells for Type 1 Diabetes).
• Bone Marrow Transplants: A standard, FDA-approved treatment where adult hematopoietic multipotent stem cells are infused into patients to replace bone marrow destroyed by chemotherapy in leukemia and lymphoma patients.
• Drug Testing and Development: Before testing new drugs on humans or animals, scientists can use stem cells to grow functional human tissues (like liver or heart cells) in a petri dish. Drugs are tested on these tissues to accurately gauge toxicity and efficacy in human biology.
• Understanding Disease Mechanisms: By reprogramming a patient's own diseased adult cells back into stem cells (Induced Pluripotent Stem Cells - iPSCs), scientists can watch the disease develop in a dish, identifying exact genetic defects and molecular pathways causing conditions like Alzheimer's or ALS.

1. What is BLAST?
BLAST stands for Basic Local Alignment Search Tool. It is the most universally used algorithm and software program in bioinformatics, provided primarily via the NCBI website. It allows researchers to compare a query biological sequence (either DNA, RNA, or protein) against massive global databases to find regions of local similarity.

2. How BLAST Works:
BLAST is a heuristic algorithm. Instead of doing a slow, mathematically perfect full-length comparison, it optimizes for speed. It breaks the query sequence into short "words" (e.g., 3 amino acids long). It rapidly scans the database for exact matches to these words (called "hits"). Once a hit is found, it attempts to extend the alignment outward in both directions to find a High-scoring Segment Pair (HSP). Matches are assigned a statistical significance score called the E-value (Expect value); a lower E-value means the match is highly significant and not due to random chance.

3. Key Variants of BLAST:

• blastn: Compares a nucleotide query against a nucleotide database.
• blastp: Compares a protein query against a protein database.
• blastx: Translates a nucleotide query into all 6 reading frames and compares it to a protein database.
• tblastn: Compares a protein query against a dynamically translated nucleotide database.

4. Applications and Uses of BLAST:

• Identifying Unknown Species: If a scientist sequences DNA from an unknown bacteria, running a BLAST search against the GenBank database will instantly identify the species by finding the closest match.
• Inferring Protein Function: If a newly discovered gene produces a protein of unknown function, BLAST can find structurally similar proteins in other organisms whose functions are already known, allowing researchers to infer the new protein's role.
• Evolutionary Studies (Phylogenetics): By finding similar genes (homologs) across different species (e.g., humans, mice, fruit flies), scientists can trace evolutionary lineages and construct phylogenetic trees.
• Primer Design Verification: Before performing PCR, researchers use BLAST to ensure their synthetic DNA primers only bind to the specific target gene and will not accidentally bind elsewhere in the genome.

PART A: The Process of Transcription
Transcription is the first major step of gene expression, where the information encoded in a specific segment of DNA (a gene) is copied into a complementary single-stranded messenger RNA (mRNA) molecule. It occurs in the nucleus of eukaryotes. It has three stages:

• 1. Initiation: The enzyme RNA Polymerase binds to a specific regulatory DNA sequence called the promoter (often containing a TATA box). The enzyme unwinds the DNA double helix, creating a transcription bubble.
• 2. Elongation: RNA Polymerase moves along the template DNA strand in the 3' to 5' direction, reading the bases. It synthesizes a new RNA strand in the 5' to 3' direction by adding complementary RNA nucleotides (Adenine pairs with Uracil, Cytosine pairs with Guanine).
• 3. Termination: When RNA Polymerase reaches a specific terminator sequence at the end of the gene, the enzyme detaches from the DNA, and the newly synthesized RNA transcript is released.

PART B: Post-Transcriptional Processing
In eukaryotes, the immediate product of transcription is a raw precursor called pre-mRNA. This pre-mRNA is non-functional and cannot leave the nucleus until it undergoes three critical processing modifications to become mature mRNA:

• 1. 5' Capping: A modified guanine nucleotide (7-methylguanosine) is added to the 5' end of the transcript. This cap protects the mRNA from degradation by exonucleases and acts as an attachment signal for the ribosome during translation.
• 2. Poly-A Tailing: An enzyme adds a long string of 100-250 adenine nucleotides (a Poly-A tail) to the 3' end. This tail further stabilizes the mRNA and assists in its export out of the nucleus into the cytoplasm.
• 3. RNA Splicing: Eukaryotic genes contain coding regions (Exons) interrupted by non-coding "junk" regions (Introns). A molecular machine called the spliceosome cuts out all the introns and splices (glues) the exons together into one continuous, readable coding sequence.

Conclusion: Only after these three modifications is the mature mRNA allowed to exit the nucleus through a nuclear pore and travel to a ribosome for protein translation.

1. Basis (Foundation) of Artificial Neural Networks (ANN):
An Artificial Neural Network is a machine learning algorithm computationally modeled on the structural and functional biology of the human brain.
Just as the human brain consists of billions of interconnected biological neurons that process electrical signals to learn and make decisions, an ANN consists of interconnected artificial mathematical nodes (neurons). The basis of an ANN is its ability to "learn" from training data. Instead of being explicitly programmed with rules, the network processes inputs, makes a prediction, calculates the error, and adjusts the mathematical "weights" of its connections backward through the network (a process called backpropagation) to improve its future accuracy.

2. Architecture / Parts of a Neural Network:
A standard feedforward neural network consists of three main architectural parts (layers):

• Input Layer: The first layer of the network. It does not perform computations; it simply receives the raw input data (analogous to the dendrites of a biological neuron) and passes it to the next layer. Each node represents a distinct feature of the data.
• Hidden Layer(s): Located between the input and output layers. A network can have one or multiple hidden layers (multiple layers = "Deep" Learning). These nodes perform the actual mathematical computations, extracting complex patterns and features from the data.
• Output Layer: The final layer that delivers the network's prediction or classification result (e.g., outputting a "1" for Cancer or "0" for Healthy).

3. Components of an Individual Artificial Neuron:
Inside every node (except the input layer), specific mathematical components process the signal:

• Inputs ($x$): The data signals received from previous nodes.
• Weights ($w$): Each incoming connection has a weight. The weight determines the strength or importance of that specific input. Learning is essentially the process of tweaking these weights.
• Bias ($b$): An extra constant value added to the sum to help shift the activation function, allowing the model to fit the data better (similar to the y-intercept in a linear equation).
• Summation Function: The neuron calculates the weighted sum of all inputs plus the bias: $\sum (x_i imes w_i) + b$.
• Activation Function: A mathematical gate (like Sigmoid, ReLU, or Tanh) applied to the summation. It introduces non-linearity into the network, deciding whether the neuron should "fire" (pass the signal forward) or remain inactive.

1. Introduction to Humoral Immunity:
Humoral immunity is the branch of the adaptive immune system mediated by macromolecules found in extracellular fluids (humors), primarily antibodies secreted by B-lymphocytes (B-cells). Its primary function is to neutralize and destroy extracellular pathogens (like free-floating viruses and bacteria in the blood or lymph) before they can enter host cells.

2. Mechanism of Humoral Immunity (Step-by-step):

• Antigen Recognition: A naive B-cell circulates in the lymph or blood. Its surface contains thousands of B-Cell Receptors (BCRs, which are membrane-bound antibodies). When a specific BCR encounters and binds to a matching free-floating antigen (e.g., a viral spike protein), the B-cell internalizes the antigen.
• Antigen Presentation: The B-cell processes the antigen and presents fragments of it on its surface using an MHC Class II molecule.
• T-Cell Helper Activation: A specialized Helper T-cell (Th2 cell) recognizes this presented antigen-MHC complex. The T-cell binds to it and secretes chemical signals called cytokines (like Interleukins).
• Clonal Expansion: These cytokines act as a "go" signal, stimulating the B-cell to rapidly divide and multiply (clonal expansion).
• Differentiation: The cloned B-cells differentiate into two types of cells:
  • Plasma Cells: Short-lived effector factories that secrete millions of free antibodies into the bloodstream. These antibodies bind to the pathogens, neutralizing them or marking them for destruction by macrophages (opsonization).
  • Memory B-Cells: Long-lived cells that remain in the body for years, providing rapid immunity if the exact same pathogen ever infects the body again.

3. Diagrammatic Representation:
(Note to student: In an exam, you should physically draw this flowchart/diagram)

[Pathogen in Bloodstream] 
         |
         v
[Naive B-Cell] --- (BCR binds to Antigen) ---> [Internalizes & Presents Antigen on MHC-II]
         |
         v
[Helper T-Cell (Th2)] --- (Recognizes MHC-II complex & releases Cytokines) ---> 
         |
         v
(Clonal Expansion & Differentiation of B-Cell)
         |
    +----+----+
    |         |
    v         v
[Plasma Cells]  [Memory B-Cells]
    |               |
    v               v
(Secrete free     (Dormant; wait for
 Antibodies)       future infections)
    |
    v
[Antibodies neutralize pathogen]
              

1. What are Sequence Databases?
Biological sequence databases are massive, centralized computer repositories where scientists upload, store, and access the linear alphanumeric sequences of biological macromolecules (Nucleic acids like DNA/RNA, and Proteins). These databases are the foundation of modern bioinformatics.

2. Types of Sequence Databases:
Sequence databases are primarily categorized into two main biological types:
A. Nucleotide (DNA/RNA) Sequence Databases:
These store the A, T, C, G nucleotide codes of genes and entire genomes. The three major primary databases form the International Nucleotide Sequence Database Collaboration (INSDC). They mirror each other and share data daily:

• GenBank: Maintained by the National Center for Biotechnology Information (NCBI) in the USA.
• EMBL-Bank: Maintained by the European Bioinformatics Institute (EBI) in the UK.
• DDBJ (DNA Data Bank of Japan): Maintained in Japan.

B. Protein Sequence Databases:
These store the linear sequences of the 20 standard amino acids that make up proteins.

• UniProtKB (Universal Protein Resource Knowledgebase): The central global hub for protein sequence and functional information. It is divided into two sections:
  • Swiss-Prot: High-quality, manually curated, and heavily annotated by human biologists.
  • TrEMBL: Computationally translated sequences from the INSDC databases, awaiting manual curation.
• PIR (Protein Information Resource): An integrated public bioinformatics resource to support genomic and proteomic research.

3. Uses and Applications of Sequence Databases:

• Sequence Alignment & Identification: Using tools like BLAST to compare an unknown DNA snippet against GenBank to instantly identify the organism it belongs to.
• Phylogenetic Analysis: Retrieving the sequences of a specific gene (like 16S rRNA) from multiple different species to build an evolutionary tree mapping their shared ancestry.
• Primer Design: Accessing exact viral or bacterial genomic sequences to design synthetic PCR primers for diagnostic tests (like COVID-19 RT-PCR testing).
• Functional Annotation: If a new genome is sequenced, algorithms use these databases to find open reading frames (ORFs) and compare them to known proteins to predict what functions the new genes might serve.
• Vaccine and Drug Design: Accessing the precise amino acid sequences of viral surface proteins (like the SARS-CoV-2 Spike protein) allows scientists to computationally design mRNA vaccines without needing the physical virus in the lab.

Introduction (The Paradox of Genetic Identity):
Inside any given human body, a skin cell (epithelial cell) and a nerve cell (neuron) contain the exact same DNA (the exact same 46 chromosomes and identical genomic sequence). However, they look completely different, behave differently, and perform vastly different functions. This phenomenon is known as cellular differentiation.

1. Fundamental Cause of Differences: Gene Expression
The primary reason they are different is Differential Gene Expression. While both cells have the entire "instruction manual" (DNA genome), they only read and express specific chapters (genes).
- A skin cell will turn on genes that produce Keratin (for toughness) and Melanin (for UV protection). It completely turns off the genes for neurotransmitters.
- A nerve cell will turn on genes to build ion channels, synaptic vesicles, and neurotransmitters (like dopamine), while permanently turning off keratin genes. Epigenetic tags (like DNA methylation and histone modification) lock these gene expression profiles in place.

2. Differences in Morphology (Structure & Shape):

• Skin Cell: Generally flat, tightly packed, block-like or squamous (scale-like) in shape. They form continuous sheets layered on top of each other with strong intercellular junctions (desmosomes) to create an impermeable physical barrier.
• Nerve Cell (Neuron): Highly irregular and asymmetrical. They have a central cell body (soma) with vast, sprawling branching structures. They have short branches to receive signals (dendrites) and a single, incredibly long cable-like structure (an axon) that can stretch up to a meter in length to transmit signals.

3. Differences in Function:

• Skin Cell: Acts as a physical and chemical barrier. Its primary job is protection against mechanical injury, dehydration, UV radiation, and invading microbial pathogens.
• Nerve Cell: Serves as the body's communication wiring. Its function is to generate, conduct, and transmit rapid electrical impulses (action potentials) and chemical signals across the body to coordinate movement, sensation, and thought.

4. Differences in Cell Division and Regeneration:

• Skin Cell: Highly mitotic. Skin cells are constantly sloughed off and rapidly replaced. Basal stem cells at the bottom of the epidermis divide continuously throughout a person's life to regenerate the tissue within weeks.
• Nerve Cell: Generally post-mitotic (they enter the G0 phase permanently). Once fully mature, most neurons in the central nervous system lose the ability to undergo cell division. If a neuron dies due to injury (like a stroke or spinal cord injury), it is rarely replaced, making neurological damage permanent.

5. Differences in Lifespan:

• Skin Cell: Short-lived. The journey from a basal cell to a dead, keratinized skin cell falling off the body takes about 2 to 4 weeks.
• Nerve Cell: Exceptionally long-lived. The neurons in your brain are meant to survive and function for your entire lifespan (80+ years).

Introduction to the Central Dogma of Bioinformatics:
In computational biology, a fundamental axiom is: Sequence dictates Structure, and Structure dictates Function. If two protein sequences (the primary 1D string of amino acids) are found to be highly similar when aligned (using tools like BLAST), we can draw profound conclusions about both their biological function and their evolutionary history.

(i) Justification: How their function will be similar?

• The Sequence-to-Structure Rule: Proteins do not function as straight strings; they fold into complex 3D shapes. The physical properties (size, charge, hydrophobicity) of the specific sequence of amino acids determine exactly how that protein will fold. If two proteins share a highly similar sequence, they will inevitably fold into highly similar 3D tertiary structures.
• The Structure-to-Function Rule: A protein's function (like an enzyme acting as a catalyst, or a receptor binding a hormone) is entirely dependent on the precise 3D geometry of its active sites or binding pockets (the "lock and key" model).
• Conservation of Active Sites: If the sequences are similar, the chemical environment of their active sites will be nearly identical. Therefore, they will bind the same substrates and perform the same biochemical reactions. This is why researchers use sequence similarity (homology) to predict the function of newly discovered, uncharacterized proteins.

(ii) Justification: The organisms that contain these proteins are evolutionarily related

• Homology and Common Ancestry: Sequence similarity is overwhelmingly a result of Homology—meaning the proteins descended from a shared ancestral gene. It is statistically impossible for two long, complex protein sequences (e.g., hundreds of amino acids) to be highly similar by random chance.
• The Molecular Clock Hypothesis: When two species diverge from a common ancestor, the identical genes they inherited begin to independently accumulate random mutations over millions of years. However, critical functional regions of the protein face strong purifying selection (mutations there are lethal and weeded out), keeping the sequences similar.
• Quantifying Evolutionary Distance: The degree of similarity acts as a molecular clock. If the sequences are 99% identical (like human and chimpanzee hemoglobin), it means the organisms shared a very recent common ancestor. If they are only 40% similar (like human and yeast cytochromes), it means they are evolutionarily related but diverged billions of years ago.
• Phylogenetic Trees: By comparing the sequence similarities of a conserved protein across dozens of different organisms, computational biologists construct phylogenetic trees that perfectly map the evolutionary family tree of life on Earth.