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
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 ...
Meet your teaching assistants
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
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
After today, you should be able to
Define computational biology and explain its interdisciplinary nature
What is computational biology?
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
Genetic sequences of healthy and Alzheimer patients
Find genetic risk factors
Data
Information
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
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
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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)
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
BIOSC 1540: L0.0 (Introduction)
By aalexmmaldonado
