This document summarizes Andrew Grimm's research using programming to understand HIV and AIDS. It discusses how HIV hijacks cells to reproduce, causing AIDS if left untreated. Grimm studies two types of HIV mutations - point mutations changing single letters in the genome, and recombinations swapping portions of the two genome copies. Studying mutations helps understand how HIV escapes the immune system and becomes drug-resistant. Grimm analyzes virus sequence data from laboratory experiments to compare original and mutated genomes and gain new insights into HIV, facing challenges as his analyses have expanded to millions of sequences.

1. Curing (医する)
AIDS,
with programming
Andrew Grimm

2. Curing AIDS
Understanding (理
解する) HIV,
with programming
Andrew Grimm

3. What's AIDS?
• Disease caused by HIV
• Unless treated (治療する), damages (損傷する) the
immune system (免疫系)
• Damage of immune system can cause death (死)

4. What’s HIV?
• Virus (病毒)
o Cannot live (生き残る) independently (単独で)
o Hijacks (乗っ取る) the cells (細胞) of living creatures (生体) to reproduce (
生殖) itself
• Genome (ゲノム) is 9749 letters (文字) long
o Human (人間) genome is 3 billion (30 億) letters long
• Has two copies of the genome
o Humans also have two copies of their genome

5. Impact (影響) of AIDS
Prevalence Annual deaths (死/年)
Worldwide (世界的) 35 million (3500万) 1.5 million (150万)
Australia 18,000 100
Japan 8,100 100

6. What am I studying (研
究)?
• Two types of mutation (変異)
• Point mutation (点突然変異)
• Recombination (遺伝的組換え)

7. Point mutation
• One letter (文字) of the genome (ゲノム) changing
to another letter

8. Recombination
• Swapping equivalent portions of the two copies of
the genome

9. Why study (研究)
mutation (変異)?
• It enables HIV to escape (免れる) the immune
system (免疫系)
• It enables HIV to become resistant (耐性) to drugs

10. Laboratory (実験室)
component
• Start with viruses with a known genome
• Infect (感染させる) cells with viruses
• Let them reproduce (生殖) for one generation (世代)
• Determine the sequence of new viruses
• None of this done by me!

11. Analysis component
• Compare sequences against the sequences of the
original

12. Challenges (障害) faced

13. New questions and
analyses
• Questions lead to new analyses
• New analyses lead to new insights
• New insights lead to new questions

14. Performance (性能)
• Initially only dealt with hundreds (100s) of sequences
• Now deal with millions (100万s) of sequences

15. Breaking of assumptions
• I used to assume a sequence would be either wild
type or marker type, or a mixture
• Now I have to handle wild type or marker type 1 or
marker type 2

16. Questions?
• RubyConf Australia http://www.rubyconf.org.au
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