the bioinformatics chat

#70 Prioritizing drug target genes with Marie Sadler

In this episode, Marie Sadler talks about her recent Cell Genomics paper, Multi-layered genetic approaches to identify approved drug targets. Previous studies have found

#69 Suffix arrays in optimal compressed space and δ-SA with Tomasz Kociumaka and Dominik Kempa

Today on the podcast we have Tomasz Kociumaka and Dominik Kempa, the authors of the preprint Collapsing the Hierarchy of Compressed Data Structures: Suffix Arrays in Opti

#68 Phylogenetic inference from raw reads and Read2Tree with David Dylus

In this episode, David Dylus talks about Read2Tree, a tool that builds alignment matrices and phylogenetic trees from raw sequencing reads. By leveraging the database of

#67 AlphaFold and variant effect prediction with Amelie Stein

This is the third and final episode in the AlphaFold series, originally recorded on February 23, 2022, with Amelie Stein, now an associate professor at the University of

#66 AlphaFold and shape-mers with Janani Durairaj

This is the second episode in the AlphaFold series, originally recorded on February 14, 2022, with Janani Durairaj, a postdoctoral researcher at the University of Basel.

#65 AlphaFold and protein interactions with Pedro Beltrao

In this episode, originally recorded on February 9, 2022, Roman talks to Pedro Beltrao about AlphaFold, the software developed by DeepMind that predicts a protein’s 3D st

#64 Enformer: predicting gene expression from sequence with Žiga Avsec

In this episode, Jacob Schreiber interviews Žiga Avsec about a recently released model, Enformer. Their discussion begins with life differences between academia and indus

#63 Bioinformatics Contest 2021 with Maksym Kovalchuk and James Matthew Holt

The Bioinformatics Contest is back this year, and we are back to discuss it! This year’s contest winners Maksym Kovalchuk (1st prize) and Matt Holt (2nd prize) talk abou

#62 Steady states of metabolic networks and Dingo with Apostolos Chalkis

In this episode, Apostolos Chalkis presents sampling steady states of metabolic networks as an alternative to the widely used flux balance analysis (FBA). We also discuss

#61 3D genome organization and GRiNCH with Da-Inn Erika Lee

In this episode, Jacob Schreiber interviews Da-Inn Erika Lee about data and computational methods for making sense of 3D genome structure. They begin their discussion by

#60 Differential gene expression and DESeq2 with Michael Love

In this episode, Michael Love joins us to talk about the differential gene expression analysis from bulk RNA-Seq data. We talk about the history of Mike’s own differenti

#59 Proteomics calibration with Lindsay Pino

In this episode, Lindsay Pino discusses the challenges of making quantitative measurements in the field of proteomics. Specifically, she discusses the difficulties of com

#58 B cell maturation and class switching with Hamish King

In this episode, we learn about B cell maturation and class switching from Hamish King. Hamish recently published a paper on this subject in Science Immunology, where he

#57 Enhancers with Molly Gasperini

In this episode, Jacob Schreiber interviews Molly Gasperini about enhancer elements. They begin their discussion by talking about Octant Bio, and then dive into the surpr

#56 Polygenic risk scores in admixed populations with Bárbara Bitarello

Polygenic risk scores (PRS) rely on the genome-wide association studies (GWAS) to predict the phenotype based on the genotype. However, the prediction accuracy suffers wh

#55 Phylogenetics and the likelihood gradient with Xiang Ji

In this episode, we chat about phylogenetics with Xiang Ji. We start with a general introduction to the field and then go deeper into the likelihood-based methods (maximu

#54 Seeding methods for read alignment with Markus Schmidt

In this episode, Markus Schmidt explains how seeding in read alignment works. We define and compare k-mers, minimizers, MEMs, SMEMs, and maximal spanning seeds. Markus al

#53 Real-time quantitative proteomics with Devin Schweppe

In this episode, Jacob Schreiber interviews Devin Schweppe about the analysis of mass spectrometry data in the field of proteomics. They begin by delving into the differe

#52 How 23andMe finds identical-by-descent segments with William Freyman

In this episode, Will Freyman talks about identity-by-descent (IBD): how it’s used at 23andMe, and how the templated positional Burrows-Wheeler transform can find IBD seg

#51 Basset and Basenji with David Kelley

In this episode, Jacob Schreiber interviews David Kelley about machine learning models that can yield insight into the consequences of mutations on the genome. They begin