📗 -> 01/07/25: ECS124-L1

[Lecture Slide Link]

🎤 Vocab

❗ Unit and Larger Context

Important to Frid, her background is there

3-4 assignments
4-5 timed online quizzes
2 midterms
1 final

Goals

Role / Utility of bioinformatics in modern bio
Learn basic biological, mathamatical, and algorithmic concepts
Master common bioinformatical terms
Do simple programming
- PERL??? LOL
- Other languages too (striving for language agnostic)
Computational Biology vs. Bioinformatics
- Scope of Comp. Biology?
  - Modeling processes: modeling based on biological knowledge
- Bioinformatics?
  - Applications of algorithms and statistical techniques to interpret biological data
    => leads to understanding biological organization of behavior
    How we interpret / obtain info in biology:

Observation driven
Hypothesis -> Exp.
Theory
or…
Large scale, high-throughput data accumulation
- Also a form of observation! Just done with a computer in place of human

✒️ -> Scratch Notes

T1. Sequence alignment

Used in many places:

Phylogeny, also species finding
Relationships
Migration projects
Genome sequencing
Genome assembly
Algorithmically:
Dynamic programming

T2. Database Search

Used:

BLAS, searches all DNA
Function similarity (if other similar things create red blood cells, likely this one does too)
Motif finding
Algorithmically:
Hashing alignment

T3. Gene Assembly

Used:
Algorithmically:

Graph algorithms
Alignment

Gene assembly and alignment:

Copies strand
Blows it up
Reads characters chunks at a time (100)
If you can read enough characters and find where they overlap, you can rebuild the original
Gluing them together (rebuilding) is graph theory

T4. Exact String Matching

Uses:

Finding transposable elements
Gene search
Algorithmically:
122B: Suffix Trees

MACHINE LEARNING SECTION

1. Clustering

K-Means, Hierarchical Clustering

2. Classification

Naive Bayes,

Have background data on DNA of people with and without cancer

Use ML to predict future DNA of unlabeled people
Estimate probability of both possibilities
Later find out about Broca’s Gene associated

3. Phyloenetics

Jukes cantor?
Ultra metric trees
Nearest Neighbors

4. HMM DP

Tree of knowledge expansion?

Biological knowledge - DNA mutates
|
Biological Model - Replicate, mutation rate
|
Mathematical Model and Assumptions - Comp. Biology
|
Mathematical Problem, I/O Description
|
Algorithmic Problem / Solution - Transforms input INTO output

This level is the focus of the course, high level algorithmic overview
|
Programming problem - Grunt work of building the code out
Done in labs

Counting reminder:

Stages of experiment

If experiment has multiple stages stage with outcomes respectively,

Stage # outcomes is
Total sample space size is

EX) If sequence,

Picking

How many ways can i select president and VP from a sample 130?

What about just 2 founders, no roles?

Dividing by the possible reorderings, that are equivalent orderless
= 130 * 129 / 2

How many ways to create out of 140 subjects such mating group consists of 3 subjects

140 choose 3.
How many possible mitochondrial sequences (hypothetically 300 long) can exist? Probability of 2 identical sets?

Sequence Alignment

“FACT” (assumption)

High DNA / RNA / Protein sequence similarity implies significant function or structural similarity
Similar sequence implies similar function/structure
- In RNA it might not be the function, but the structure implied

🧪 -> Refresh the Info

Did you generally find the overall content understandable or compelling or relevant or not, and why, or which aspects of the reading were most novel or challenging for you and which aspects were most familiar or straightforward?)

Did a specific aspect of the reading raise questions for you or relate to other ideas and findings you’ve encountered, or are there other related issues you wish had been covered?)

Vault

Explorer

ECS124-L1