BIOSC 1540: L0.0 (Introduction)

Computational Biology

Lecture 0.0

(BIOSC 1540)

Aug 26, 2025

Course Overview

After today's lecture, you should have a better understanding of ...

Your teaching team

The instructor

Alex Maldonado, PhD

he/him

Acceptable ways to address me:

Alex (preferred)

Dr. Maldonado

Dr. M

Office hours: TBD

Email: alex.maldonado@pitt.edu

Ph.D. in Chemical Engineering, 2023
University of Pittsburgh

B.S.E in Chemical Engineering, 2018
Western Michigan University

Position: Assistant Teaching Professor

My website

aalexmmaldonado.com

Alex's fun facts

Every male in my (maternal) family played football

—I rebelled

Alex's fun facts

Part-time jobs during college

Construction
UPS package handler
Kent County Traffic safety
Jimmy John's delivery driver
Wings West ice events

Tessa the Princessa

Get to know my ...

Movie taste

Music taste

Meet your teaching assistants

More information

Thursdays

3:00 - 4:00 pm in L10 Clapp

Caelyn Peppler (Any)

Mariska Goswami (she/her)

Mondays

Justine Denby (she/her)

Rushali Patel (she/her)

11:00 am to 12:00 pm in 102 Clapp

Wednesdays

1:00 to 2:00 pm in L1 Clapp

Priyam Chauhan (she/her)

Jay Grimsdall (he/they)

César Guerra-Solano (he/him)

CByte UTA

(More on this later)

After today's lecture, you should have a better understanding of ...

Course structure, expectations, and available resources for success

Single source of truth

All course materials will be posted on this website: pitt-biosc1540-25f.oasci.org/

Why?

There are few comprehensive resources for this rapidly changing field

Things that contain student information will be only on Canvas to be FERPA compliant

Assignments will be submitted on Gradescope

Assessments and grade distribution

We will have ...

Four 15-minute quizzes (28%)
13 project-based assignments (72%)

Rationale:
(1) Hands-on projects are key for mastering material.
(2) Quizzes prove your comprehension without outside help.

Minimum quiz average:

To pass the course with a C or higher, your quiz average must be at least 73%. If your quiz average is below 73%, your overall course grade will be capped at a C–, regardless of your project grades.

Rationale:

This reduces the impact of quizzes on your grade while still requiring that you understand the material

Late penalties

\text{\% Penalty} = 0.01 (2.083 \times \text{hours late})^{2}

Hours late	Penalty
6	1.6%
12	6.2%
24	25.0%
36	56.2%
48	100.0%

We have a forgiving late penalty for a few hours but it rapidly increases after 12 hours

Typically, it is in your best interests to take a few more hours to do your best work

Semester overview

2. Transcriptomics

1. Genomics

3. Computer-aided drug design

4. Molecular simulations

Bioinformatics

Modules

Computational Structural Biology

Where do we get our insight from?

Critical thinking is paramount and happens outside your comfort zone

How does this influence my teaching?

I primarily focus on the top of Bloom's taxonomy, more akin to computer science and engineering courses

Few points

Many points

Challenging problems are worth fewer points to encourage creative problem solving

Computational Bytes (CBytes) are optional, bite-sized programming challenges tailored to computational biology

Objective: Encourage you to interact more deeply with the course material without a direct impact on your grade

Gamification and incentives: Gradescope autograder will be used to award "Advanced Training Points" (ATP) to students who participate within two weeks of a CByte's release

Rewards: Cumulative ATP can be used to redeem class-wide rewards.
For example, everyone can drop an assignment or quiz or extend a deadline.

First one will be released Jan 17th

César Guerra-Solano was awarded the Chancellor's Undergraduate Teaching Fellowship to develop these CBytes

(See Advent of Code.)

After today, you should be able to

Define computational biology and explain its interdisciplinary nature

What is computational biology?

Any application of computational methods to obtain insight into biological phenomena.

My definition . . .

My main categories . . .

Bioinformatics

Computational structural biology

Bioinformatics deals with untangling big data for biological insights

Credit

Genetic sequences of healthy and Alzheimer patients

Find genetic risk factors

Data

Information

Credit

Data

Information

mRNA of cancer cells in a tumor

Early detection of benign to cancerous cell transition

Bioinformatics deals with untangling big data for biological insights

Credit

Phenomena

Representation

Modeling employs physical representations that mimic key biological phenomena

Protein-protein binding

Classical force fields

After today, you should be able to

Understand the balance between applications and development

Computational Biology is broad

Data science

Computer science

Biology

Physics/
Engineering

Chemistry/
Biochemistry

Mathematics

You can tailor your career to these interests

We will touch on all of these topics in this course

Method development or applying tools?

Computer science

Biology

Developing

Applying

Typically, it is harder to pick up after the fact (a different way of thinking)

Many, many, many specalities

Both separately are pretty saturated

Before the next class, you should

P01A will be released tomorrow and is due Jan 17th
- You should start Intro to Programming on Kaggle
Check that you are subscribed to Canvas notifications

Lecture 02A:
DNA sequencing - Foundations

Lecture 01:
Computational biology overview

Today

Tuesday

There are two types of programming languages

Credit

Credit

Compiled

Interpreted

E.g., Mojo, Rust, Zig, Go, C, C++

E.g., Python and R

There are some exceptions: Java, Julia

*

After today, you should be able to

Identify key applications and recent advancements

AlphaFold 3

"AlphaFold 3 can predict the joint structure of complexes including proteins, nucleic acids, small molecules, ions, and modified residues."

HOMER2

"We show that the effect of transcription factor binding on transcription initiation is position dependent."

Miniprot: protein-genome aligner

"Miniprot [...] is tens of times faster than existing tools while achieving comparable accuracy on real data."

Why would we use protein-genome instead of genome-genome mapping?

TopHat: 983999

A. Protein-genome mapping is more sensitive for detecting distant homologs
B. Genome-genome mapping is too slow for large-scale comparisons
C. Protein–genome mapping can detect all forms of RNA editing events automatically
D. Genome-genome mapping cannot handle intron-exon structures

(Not for points)

After today, you should be able to

Navigate Google Colab

(If time permits)

Python worksheet
(time permitting)

After today, you should be able to

Identify potential career paths and educational opportunities

Bioinformatics Scientist

Description: Develops software tools and approaches for analyzing biological data, particularly genomic and proteomic data.

Expected Salary: $80,000 - $130,000

Qualifications:

PhD in Bioinformatics, Computational Biology, or related field
Strong programming skills (Python, R, C++)

Example companies: UPMC, Illumina, 23andMe, Genentech, Regeneron Pharmaceuticals, Broad Institute

Computational Biologist

Description: Applies computational methods to study biological systems, often focusing on modeling complex biological processes.

Expected Salary: $75,000 - $135,000

Qualifications:

PhD in Computational Biology, Systems Biology
Expertise in mathematical modeling and simulation
Strong programming and data analysis skills

Example companies: Moderna, Vertex Pharmaceuticals, Biogen, Allen Institute for Brain Science, Flatiron Health

Biostatistician

Description: Applies statistical methods to analyze biological and health-related data, often in clinical trials or epidemiological studies.

Expected Salary: $72,000 - $119,000

Qualifications:

Master's or PhD in Biostatistics or related field
Strong background in statistics and mathematical modeling
Proficiency in statistical software (R, SAS, STATA)

Example companies: Pfizer, Merck, Johnson & Johnson, IQVIA, Fred Hutchinson Cancer Research Center

Molecular Modeler

Description: Uses computational methods to model and simulate molecular structures and interactions, often in drug discovery.

Expected Salary: $85,000 - $140,000

Qualifications:

PhD in Computational Chemistry, Biophysics, or related field
Experience with molecular dynamics simulations
Knowledge of drug design principles

Example companies: Schrödinger, Novartis, GlaxoSmithKline (GSK), Atomwise, Dassault Systèmes BIOVIA

If these careers sound interesting, a PhD should be on your radar

Note: There tend to be more jobs in bioinformatics than simulation and modeling

Okay, but what about just a Bachelor's degree?

Challenging for computational biology jobs, but other options are available

Focus on one-half of your major

I'm unfamiliar with options here (your advisors are well-versed)

Computer Science

Biology

Software engineer, data science, machine learning, web development

What will help you prepare for

Everyone applying for the same positions has a college degree

Distinguish yourself with extracirriculars

Employers and graduate schools do not care about the classes you took, they care about what you can do

?

How to do this?

Show and tell

Your marketable skills are learned outside the classroom

Computer science: Python, GitHub, machine learning, Rust

Graphic design: Illustrator/Inkscape, Photoshop/Gimp, Blender

Communication: Writing and presenting

Classes give foundational knowledge to learn hands-on skills in research and internships

Computational biology: You will get a small taste of this in classes; you need some research or project experience