#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...
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the bioinformatics chat
A podcast about computational biology, bioinformatics, and next generation sequencing.
Episodes
20 of 70 episodes#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 St...
#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....
#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...
#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 research...
#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 t...
#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 differe...
#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 Ma...
#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 a...
#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. T...
#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 his...
#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 dis...
#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 i...
#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...
#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...
#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 l...
#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 max...
#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 beg...
#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-Whe...
#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 mutat...