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 different types of mass spectrometry methods, including MS1,
MS2, and, MS3, and the reasons for using each...
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 segments in the presence of
genotyping and phasing errors.
Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform
(William A. Freyman, Kimberly F. McManus, Suyash S. Shringarpure, Ethan M...
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 their discussion by talking about
Calico Labs, and then delve into a series of papers that David has
written about using models, named Basset and Basenji, that connect genome
sequence to functional activity and so can be used to quantify the effect of
In this episode, Jacob Schreiber interviews Jill Moore about
recent research from the ENCODE Project. They begin their
discussion with an overview and goals of the ENCODE Project, and then
discuss a bundle of papers that were recently published in various
Nature journals and the flagship paper, Expanded encyclopaedias of DNA elements in the human and mouse genomes...
In systems biology, Boolean networks are a way to model interactions such as
gene regulation or cell signaling. The standard
interpretations of Boolean networks are the synchronous, asynchronous, and
fully asynchronous semantics.
In this episode, Loïc Paulevé explains how the
same Boolean networks can be interpreted in a new, “most permissive” way...
In this episode, Jacob Schreiber interviews Marinka Zitnik about
applications of machine learning to drug development.
They begin their discussion with an overview of open research questions in the
field, including limiting the search space of high-throughput testing methods,
designing drugs entirely from scratch, predicting ways that existing drugs can
be repurposed, and identifying likely side-effects of combining existing drugs
in novel ways...
NGLess is a programming language specifically
targeted at next generation sequencing (NGS) data processing.
In this episode we chat with its main developer, Luis Pedro
Coelho, about the benefits of domain-specific
languages, pros and cons of Haskell in bioinformatics, reproducibility, and of
course NGLess itself...
In this episode, I continue to talk (but mostly listen) to Sergey Koren and Sergey Nurk.
If you missed the previous episode, you should probably start there.
Otherwise, join us to learn about HiFi reads, the tradeoff between read length
and quality, and what tricks HiCanu employs to resolve highly similar repeats...
In this episode, Sergey Nurk and Sergey Koren from the NIH share their thoughts
on genome assembly. The two Sergeys tell the stories behind their amazing
careers as well as behind some of the best known genome assemblers: Celera
assembler, Canu, and SPAdes.
Porcupine is a molecular tagging system—a way to tag physical
objects with pieces of DNA called molecular bits, or molbits for short.
These DNA tags then can be rapidly sequenced on an Oxford Nanopore MinION
device without any need for library preparation.
In this episode, Katie Doroschak explains how Porcupine works—how molbits
are designed and prepared, and how they are directly recognized by the
software without an intermediate basecalling step...