BIF402 — Ethical and Legal Issues in Bioinformatics: Midterm & Finalterm Solved MCQs and Subjective

This solved paper covers BIF402 — Ethical and Legal Issues in Bioinformatics for Virtual University of Pakistan students, with midterm (Lectures 1–22) and finalterm (Lectures 23–45) questions solved with answers. It includes 10 midterm MCQs, 10 finalterm MCQs, 5 midterm subjective questions and 5 finalterm subjective questions — 30 questions in total — covering ethics and law in bioinformatics, genomic privacy, consent, GINA and gene patenting. Every answer was solved independently and cross-checked against the VU handout, with the handout lecture cited under each question; handout page numbers are being added as they are verified. Use the Take the BIF402 quiz link below to practise all 20 MCQs interactively with a live score counter. See the Solved MCQs page and the midterm and finalterm mega hubs for solved papers for every subject. Compiled and verified by Virtual Ustaad. Last updated: 6 November 2026.

1. Midterm Solved MCQs

Q1. Bioinformatics ethics is mainly concerned with:
A) How fast a computer can run BLAST
B) The moral and legal questions raised by collecting, storing, analysing and sharing biological — especially genomic — data
C) The price of DNA sequencing machines
D) The design of laboratory buildings
Correct answer: B — The moral and legal questions raised by collecting, storing, analysing and sharing biological — especially genomic — data
Reference: VU handout — Introduction to ethics in bioinformatics. Lecture — not confirmed in source. Page — not confirmed in source.

Q2. Informed consent in genomic research means that a participant:
A) Signs any form without reading it
B) Voluntarily agrees to take part after understanding the purpose, procedures, risks, benefits and how their data will be used and shared
C) Is paid to take part
D) Gives a blood sample only
Correct answer: B — Voluntarily agrees to take part after understanding the purpose, procedures, risks, benefits and how their data will be used and shared
Reference: VU handout — Informed consent. Lecture — not confirmed in source. Page — not confirmed in source.

Q3. The Belmont Report (1979) sets out three core ethical principles for research involving human subjects. They are:
A) Honesty, courage and loyalty
B) Respect for persons, beneficence and justice
C) Privacy, profit and publicity
D) Speed, accuracy and cost
Correct answer: B — Respect for persons, beneficence and justice
Reference: VU handout — Research ethics; Belmont Report. Lecture — not confirmed in source. Page — not confirmed in source.

Q4. An Institutional Review Board (IRB) / ethics committee is responsible for:
A) Funding research
B) Reviewing research proposals to protect the rights, safety and welfare of human participants
C) Publishing papers
D) Selling DNA data
Correct answer: B — Reviewing research proposals to protect the rights, safety and welfare of human participants
Reference: VU handout — Research ethics; IRB. Lecture — not confirmed in source. Page — not confirmed in source.

Q5. The HeLa cell line, one of the most widely used in research, was derived from cells taken from Henrietta Lacks in (1951):
A) With her full informed consent and a signed agreement
B) Without her knowledge or consent
C) After her family was paid for them
D) From a public database
Correct answer: B — Without her knowledge or consent
Reference: VU handout — Landmark cases; Henrietta Lacks. Lecture — not confirmed in source. Page — not confirmed in source.

Q6. Why is genomic data especially sensitive as personal data?
A) It is very large
B) It is unique to an individual, reveals information about their relatives as well, and cannot be changed if it is leaked
C) It is stored only on paper
D) It is worthless to insurers
Correct answer: B — It is unique to an individual, reveals information about their relatives as well, and cannot be changed if it is leaked
Reference: VU handout — Genomic data privacy. Lecture — not confirmed in source. Page — not confirmed in source.

Q7. 'De-identification' of genomic data means:
A) Deleting the data
B) Stripping direct identifiers (such as name) from the data before sharing it, so it cannot readily be linked to an individual
C) Encrypting the data with a password only the researcher knows
D) Publishing the data with the participant's name
Correct answer: B — Stripping direct identifiers (such as name) from the data before sharing it, so it cannot readily be linked to an individual
Reference: VU handout — Data privacy; de-identification. Lecture — not confirmed in source. Page — not confirmed in source.

Q8. A key limitation of anonymising genomic data is that:
A) It makes the data too large
B) A genome is itself an identifier — anonymised data can sometimes be re-identified by matching it against other databases (e.g. genealogy databases)
C) It is illegal in all countries
D) It destroys the DNA sample
Correct answer: B — A genome is itself an identifier — anonymised data can sometimes be re-identified by matching it against other databases (e.g. genealogy databases)
Reference: VU handout — Privacy and re-identification. Lecture — not confirmed in source. Page — not confirmed in source.

Q9. The 'Golden State Killer' case (2018) is used in bioinformatics ethics to illustrate:
A) That DNA evidence is never useful
B) That genetic genealogy databases built for one purpose (finding relatives) can be used for another (law-enforcement identification) — raising consent and privacy questions
C) That all criminals should be sequenced
D) That genealogy databases are always private
Correct answer: B — That genetic genealogy databases built for one purpose (finding relatives) can be used for another (law-enforcement identification) — raising consent and privacy questions
Reference: VU handout — Landmark cases; forensic genealogy. Lecture — not confirmed in source. Page — not confirmed in source.

Q10. Which of the following is an ethical issue specific to bioinformatics research, rather than to laboratory bench work alone?
A) Who owns and controls a person's genome sequence and the information in it, and who decides how it is used
B) Whether a pipette is calibrated
C) Whether a laboratory coat is worn
D) The temperature of a freezer
Correct answer: A — Who owns and controls a person's genome sequence and the information in it, and who decides how it is used
Reference: VU handout — Ethics of bioinformatics research. Lecture — not confirmed in source. Page — not confirmed in source.

2. Finalterm Solved MCQs

Q1. The Genetic Information Nondiscrimination Act (GINA), passed in the United States in (2008), prohibits the use of genetic information in decisions about:
A) Life insurance and disability insurance
B) Health insurance and employment
C) Mortgages and car loans
D) University admissions only
Correct answer: B — Health insurance and employment
Reference: VU handout — GINA. Lecture — not confirmed in source. Page — not confirmed in source.

Q2. GINA does NOT cover which of the following?
A) Health insurance
B) Employment
C) Life insurance, disability insurance and long-term care insurance
D) Genetic testing by an employer
Correct answer: C — Life insurance, disability insurance and long-term care insurance
Reference: VU handout — GINA; limits. Lecture — not confirmed in source. Page — not confirmed in source.

Q3. In Association for Molecular Pathology v. Myriad Genetics (US Supreme Court, 2013), the Court held that:
A) Isolated naturally occurring DNA is patentable, and cDNA is not
B) A naturally occurring DNA segment is not patent eligible merely because it has been isolated, but cDNA (complementary DNA) is patent eligible because it is not naturally occurring
C) No DNA of any kind can ever be patented
D) Genes can be patented if they are discovered first
Correct answer: B — A naturally occurring DNA segment is not patent eligible merely because it has been isolated, but cDNA (complementary DNA) is patent eligible because it is not naturally occurring
Reference: VU handout — Patenting genes; Myriad. Lecture — not confirmed in source. Page — not confirmed in source.

Q4. The BRCA1 and BRCA2 genes, at the centre of the Myriad case, are associated with increased risk of:
A) Diabetes only
B) Breast and ovarian cancer
C) Heart disease only
D) Alzheimer's disease only
Correct answer: B — Breast and ovarian cancer
Reference: VU handout — Patenting genes; Myriad; BRCA. Lecture — not confirmed in source. Page — not confirmed in source.

Q5. For an invention to be patentable it must generally be:
A) New, non-obvious and useful
B) Old, obvious and useless
C) Published in a newspaper
D) Expensive to produce
Correct answer: A — New, non-obvious and useful
Reference: VU handout — Intellectual property; patent criteria. Lecture — not confirmed in source. Page — not confirmed in source.

Q6. HIPAA (the US Health Insurance Portability and Accountability Act, 1996) regulates:
A) The patenting of genes
B) The use and disclosure of protected health information, including genetic data
C) The price of medicines
D) University admissions
Correct answer: B — The use and disclosure of protected health information, including genetic data
Reference: VU handout — HIPAA. Lecture — not confirmed in source. Page — not confirmed in source.

Q7. Under the EU General Data Protection Regulation (GDPR), genetic data is treated as:
A) Ordinary, non-sensitive data
B) A special category of personal data, requiring stronger protection and a lawful basis for processing
C) Data that cannot be collected at all
D) Public data
Correct answer: B — A special category of personal data, requiring stronger protection and a lawful basis for processing
Reference: VU handout — GDPR and genetic data. Lecture — not confirmed in source. Page — not confirmed in source.

Q8. The NIH policy on sharing large-scale genomic data requires investigators to:
A) Keep all data secret forever
B) Submit de-identified data to NIH-designated repositories (e.g. dbGaP), with controlled access where the IRB requires it
C) Sell the data to the highest bidder
D) Publish participants' names with the data
Correct answer: B — Submit de-identified data to NIH-designated repositories (e.g. dbGaP), with controlled access where the IRB requires it
Reference: VU handout — Data sharing; NIH policy. Lecture — not confirmed in source. Page — not confirmed in source.

Q9. The FAIR principles for research data stand for data that are:
A) Fast, Accurate, Indexed and Reliable
B) Findable, Accessible, Interoperable and Reusable
C) Free, Anonymous, Indexed and Registered
D) Funded, Approved, Insured and Reviewed
Correct answer: B — Findable, Accessible, Interoperable and Reusable
Reference: VU handout — Data sharing; FAIR. Lecture — not confirmed in source. Page — not confirmed in source.

Q10. A bioinformatics database or software tool is most likely to be protected by:
A) A patent on the underlying natural DNA sequence alone
B) Copyright (for the code and the database structure) and, where applicable, patent or licensing terms for novel methods — not by owning the natural sequence itself
C) No legal protection at all
D) A trademark on the gene name
Correct answer: B — Copyright (for the code and the database structure) and, where applicable, patent or licensing terms for novel methods — not by owning the natural sequence itself
Reference: VU handout — Intellectual property in bioinformatics. Lecture — not confirmed in source. Page — not confirmed in source.

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3. Midterm Subjective

Q1. What is informed consent in genomic research, and why is it more difficult to obtain than consent for an ordinary medical procedure?
Answer: Informed consent means a participant voluntarily agrees to take part after understanding the purpose, procedures, risks, benefits, and how their data will be used, stored and shared — including future uses that may not yet be known. It is harder in genomic research for four reasons. (1) The information is permanent and identifying: a genome cannot be changed, and it identifies the person and their relatives. (2) Future uses are unknown: data deposited in a database may be used years later for research the participant never imagined, so consent given today may not cover tomorrow's uses — hence the debate over broad consent vs specific consent. (3) Incidental findings: sequencing may reveal a risk of a serious disease the participant did not ask about, raising the question of whether and how to disclose it. (4) Family implications: a participant's genome reveals information about blood relatives who never consented. Good practice therefore includes clear explanations in plain language, the right to withdraw, choices about data sharing and about receiving incidental findings, and ethics-committee (IRB) oversight.
Reference: VU handout — Informed consent in genomic research. Lecture — not confirmed in source. Page — not confirmed in source.

Q2. Explain the three Belmont principles and apply each one to a bioinformatics study that collects genome sequences.
Answer: The Belmont Report (1979) sets out three principles. (1) Respect for persons: individuals are autonomous and must be treated as such — so participants must give informed consent, must be told how their genome data will be used and shared, and vulnerable people (children, those who cannot consent) need extra protection. (2) Beneficence: researchers must maximise benefits and minimise harms — so a bioinformatics study should secure the data, de-identify it, limit access, and weigh the scientific value against the risk of privacy loss or discrimination. (3) Justice: the benefits and burdens of research must be fairly distributed — so the study should not exploit one group (e.g. a poor or indigenous community) to produce knowledge or profit that benefits only others, and access to any resulting tests or treatments should be fair. Together the principles explain why genomic research needs consent, data protection and fair benefit-sharing, not merely technical skill.
Reference: VU handout — Research ethics; Belmont Report. Lecture — not confirmed in source. Page — not confirmed in source.

Q3. Discuss the Henrietta Lacks / HeLa case. What ethical lessons does it hold for bioinformatics?
Answer: Henrietta Lacks was a patient who died of cervical cancer in (1951). Cells taken from her tumour — without her knowledge or consent — became the HeLa cell line, the first immortal human cell line and one of the most widely used tools in biomedical research, contributing to the polio vaccine, cancer research and many other advances. Her family learned about it decades later, and the genome of the HeLa cells was published in (2013) without the family's consent, revealing genetic information about her descendants. The lessons for bioinformatics are: (1) consent matters even when the material is 'waste' tissue — taking and using human material without permission treats the person as a means, not an end; (2) anonymisation is not enough — a genome identifies a person and their family, so publishing a genome can expose relatives who never consented; (3) benefit-sharing matters — the family of the woman whose cells generated enormous scientific and commercial value received no benefit and for many years could not afford health care; and (4) governance must catch up with technology — the case led to new agreements (in (2013) the NIH reached an agreement with the Lacks family on access to the HeLa genome). The case is the classic example of why bioinformatics needs consent, privacy and benefit-sharing rules, not just technical ones.
Reference: VU handout — Landmark cases; Henrietta Lacks. Lecture — not confirmed in source. Page — not confirmed in source.

Q4. Why is genomic privacy so hard to protect? Discuss de-identification and re-identification.
Answer: Genomic privacy is hard because a genome is simultaneously medical information and an identifier. De-identification — stripping direct identifiers such as name, address and date of birth before sharing data — is the standard protection, required by the NIH data-sharing policy and the HIPAA Privacy Rule. But it has limits. (1) The genome itself identifies: a DNA sequence is unique (except for identical twins), so anyone with a reference sample can match it. (2) Linkage attacks: an 'anonymous' genome can be linked to a person by matching it with genealogy databases, surnames inferred from Y-chromosome data, or other public records — researchers have demonstrated re-identification of participants in genomic studies. (3) Relatives are exposed: identifying one person reveals information about their parents, siblings and children. (4) The data cannot be recalled: once a genome is published or leaked, it cannot be 'unpublished' or changed like a password. The practical conclusion is that de-identification must be combined with other protections: controlled (not open) access to sensitive data, data-use agreements, secure computing environments, ethics-committee oversight, and honest communication with participants that absolute anonymity cannot be guaranteed.
Reference: VU handout — Genomic privacy; re-identification. Lecture — not confirmed in source. Page — not confirmed in source.

Q5. Who owns a person's genome? Discuss the ethical and legal arguments.
Answer: There is no single agreed answer, which is itself the problem. Arguments that the individual owns it: the genome is part of the person's body and identity; they should control who collects, uses and profits from it; this follows from autonomy and informed consent. Arguments that no one owns it: a genome is information about a natural, shared human heritage — it is also partly shared with relatives and with humanity — and treating it as property could block research and medical progress. Arguments that institutions or researchers own the data they generate: the sequencing, curation and analysis cost money and skill, and databases and companies claim rights over the datasets and tools they build — but this does not give them rights over the person's underlying genetic information. The law reflects this tension: naturally occurring DNA cannot be patented (Myriad, 2013), while inventions built on it (cDNA, tests, software, databases) can be protected; privacy laws (HIPAA, GDPR, GINA) give individuals rights over their genetic information without calling it 'ownership' in the property sense. The practical consensus in bioinformatics ethics is a bundle of rights rather than simple ownership: the right to consent, to know how data is used, to withdraw, to privacy, and to share in benefits — with clear rules for researchers and companies.
Reference: VU handout — Ownership of genomic data. Lecture — not confirmed in source. Page — not confirmed in source.

4. Finalterm Subjective

Q1. Explain GINA (2008). What does it protect against, and what are its main gaps?
Answer: The Genetic Information Nondiscrimination Act (GINA) is a US federal law signed on 21 May (2008). It prohibits health insurers from using genetic information to decide eligibility or premiums, and employers from using genetic information in hiring, firing, promotion or other employment decisions, or from requesting genetic tests. Its purpose was to remove the fear that taking a genetic test — or taking part in genomic research — could cost a person their job or their health cover, a fear that was deterring both testing and research. Its main gaps are widely noted: (1) it does not cover life insurance, disability insurance or long-term care insurance — insurers in those markets can still use genetic information; (2) it does not cover the military, the Indian Health Service or federal employees in the same way (other rules apply); (3) it does not protect against discrimination based on a disease that has already manifested (that is covered by other laws, such as the Americans with Disabilities Act); and (4) it is a US law — most countries have no equivalent, and Pakistan has no GINA-like statute, so protection depends on general privacy and anti-discrimination law. GINA is therefore an important but incomplete protection, and bioinformatics students should know both what it covers and what it leaves out.
Reference: VU handout — GINA. Lecture — not confirmed in source. Page — not confirmed in source.

Q2. Explain the Myriad Genetics case (2013) and its significance for bioinformatics.
Answer: Myriad Genetics held patents on the isolated BRCA1 and BRCA2 genes, whose mutations greatly increase the risk of breast and ovarian cancer, giving it a monopoly on testing for those genes. The Association for Molecular Pathology and others sued, arguing that human genes are products of nature and cannot be patented. In Association for Molecular Pathology v. Myriad Genetics (decided 13 June (2013)) the US Supreme Court held unanimously that a naturally occurring DNA segment is a product of nature and is not patent eligible merely because it has been isolated, but that cDNA (complementary DNA, made in the laboratory from mRNA, containing only exons) is patent eligible because it is not naturally occurring. The significance for bioinformatics is large: (1) it ended gene monopolies of the Myriad kind — after the decision, other laboratories could offer BRCA testing, prices fell and second opinions became possible; (2) it drew a line between discovery (finding a natural sequence — not patentable) and invention (creating something new, such as cDNA, a new test or a new method — patentable); and (3) it left open questions — method claims, altered DNA and the patentability of bioinformatics software and databases were not decided by the case. The case is the leading example of how patent law shapes access to genetic testing and to genomic data.
Reference: VU handout — Patenting genes; Myriad. Lecture — not confirmed in source. Page — not confirmed in source.

Q3. How should genomic data be shared? Discuss the tension between open science and privacy.
Answer: Genomic science depends on sharing: large datasets are needed to find disease genes, validate results and build useful tools, and funders such as the NIH require data sharing. But sharing conflicts with privacy, because genomic data is identifying, permanent and familial. The current compromise has several layers. (1) De-identification: strip direct identifiers before depositing data, as the NIH policy requires. (2) Tiered access: non-sensitive summary data can be openly shared, while individual-level data goes into controlled-access repositories (e.g. NIH dbGaP, the European Genome-Phenome Archive) where researchers must apply, state their purpose and sign a data-use agreement, with the IRB deciding the access level. (3) Consent and governance: participants should be told about sharing at consent, and data access committees should oversee who gets the data. (4) FAIR principles: data should be Findable, Accessible, Interoperable and Reusable — but 'accessible' means accessible under appropriate conditions, not necessarily open to everyone. (5) Technical protections: secure computing, encryption and, increasingly, federated analysis (bringing the analysis to the data rather than moving the data). The tension cannot be eliminated — it can only be managed — and the balance depends on the sensitivity of the data and the trust of participants.
Reference: VU handout — Data sharing. Lecture — not confirmed in source. Page — not confirmed in source.

Q4. Discuss intellectual property in bioinformatics: patents, copyright and databases. What can and cannot be owned?
Answer: Intellectual property in bioinformatics has three main parts. Patents protect novel, non-obvious and useful inventions — a new diagnostic test, a new method, or cDNA — but after Myriad (2013) a naturally occurring DNA sequence cannot be patented merely because it has been isolated; discovering a gene is not inventing it. Patents on genes or tests can also restrict access (Myriad's BRCA monopoly) and are therefore controversial. Copyright protects the expression of an idea, not the idea itself: the source code of a bioinformatics program, and the selection and arrangement of a database, can be copyrighted, but the underlying biological facts (a sequence, a gene's function) cannot. Databases are protected in the EU by a sui generis database right and elsewhere by contract and licensing terms; in the US, facts alone are not copyrightable, so database owners rely on licences and terms of use. The practical result is a layered system: the raw sequence is a shared scientific resource, while the tools, curated databases and applications built on it can be owned and licensed. Open-source licences (e.g. for BLAST, Bioconductor) and open databases (GenBank, Ensembl) show that much of bioinformatics works best when the underlying data and tools are shared, with IP used to protect specific inventions rather than to lock up the genome itself.
Reference: VU handout — Intellectual property in bioinformatics. Lecture — not confirmed in source. Page — not confirmed in source.

Q5. A researcher wants to use a public genealogy database to identify the relatives of a participant in a genomic study, without asking the participant. Is this ethical? Discuss.
Answer: No — not without consent and ethics approval, and the case illustrates three core problems. (1) Consent: the participant consented to the study, not to having their relatives identified through a third-party database; and the relatives never consented at all, yet their genetic information is exposed by the match. Consent is specific, not a blank cheque. (2) Privacy and re-identification: genomic data is identifying, and genealogy databases are designed to link people; using them defeats the de-identification that the study promised participants, and the Golden State Killer case shows that such secondary use is technically easy and hard to foresee. (3) Purpose limitation and trust: data collected for research should be used for the purpose for which consent was given; using it for a different purpose — especially one with legal or social consequences for a family — breaks the trust on which research participation depends and may deter future participants. The researcher should instead: seek ethics-committee (IRB) approval for any new use, re-contact the participant for specific consent, consider whether the question can be answered without identifying relatives, and follow the data-use agreement and the law (including GDPR-style purpose-limitation rules where they apply). If identification is genuinely necessary and lawful (e.g. a court order), that is a legal matter for the authorities, not a decision for the researcher alone.
Reference: VU handout — Secondary use of genomic data; forensic genealogy. Lecture — not confirmed in source. Page — not confirmed in source.