Devon Kohler

Devon Kohler

PhD candidate in computational biology, building statistical & causal methods for MS-based proteomics, with experience in RNA-seq and multi-omics integration.

Teaching

Quantitative Proteomics: Case Studies

Two-day Short Course, ASMS 2025, 2025

In Case study 1, we analyzed an SRM proteomics dataset from a case-control study of heart failure using a salt-sensitive rat model, which included biological and technical replicates. Participants explored the importance of study design (in particular of normalization and randomization), the importance of visualizing chromatograms (and signal interferences), and setting up, conducting and interpreting the results of statistical analyses in MSstats.

Statistical Analysis of Targeted Proteomics Experiments

Short Course, UW Targeted Mass Spectrometry Course, 2024

I taught a short course on quantitative proteomics, covering key concepts from standards, calibration, and statistical considerations in study design to statistical analysis of proteomics experiments. The course also included hands-on training in Panorama for data management and visualization, giving participants both the theoretical background and practical tools to design, analyze, and interpret quantitative proteomics studies with confidence.

Quantitative Proteomics: Case Studies

Two-day Short Course, ASMS 2024, 2024

In Case study 1, we analyzed an SRM proteomics dataset from a case-control study of heart failure using a salt-sensitive rat model, which included biological and technical replicates. Participants explored the importance of study design (in particular of normalization and randomization), the importance of visualizing chromatograms (and signal interferences), and setting up, conducting and interpreting the results of statistical analyses in MSstats.

Quantitative Proteomics: Case Studies

Two-day Short Course, ASMS 2023, 2023

In Case study 1, we analyzed an SRM proteomics dataset from a case-control study of heart failure using a salt-sensitive rat model, which included biological and technical replicates. Participants explored the importance of study design (in particular of normalization and randomization), the importance of visualizing chromatograms (and signal interferences), and setting up, conducting and interpreting the results of statistical analyses in MSstats.

Quantitative Proteomics: Case Studies

Two-day Short Course, ASMS 2022, 2022

In Case study 1, we analyzed an SRM proteomics dataset from a case-control study of heart failure using a salt-sensitive rat model, which included biological and technical replicates. Participants explored the importance of study design (in particular of normalization and randomization), the importance of visualizing chromatograms (and signal interferences), and setting up, conducting and interpreting the results of statistical analyses in MSstats.

Algorithms

Teachers Assistant, Northeastern University, 2019

Teacher’s Assistant for master’s level algorithms class.