the bioinformatics chat

By Roman Cheplyaka

A podcast about computational biology, bioinformatics, and next generation sequencing.... more

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FAQs about the bioinformatics chat:

How many episodes does the bioinformatics chat have?

The podcast currently has 70 episodes available.

the bioinformatics chat episodes:

December 21, 2023#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 that the drugs that target a gene linked to the
disease are more likely to be approved. Yet there are many ways to define what
it means for a gene to be linked to the disease. Perhaps the most
straightforward approach is to rely on the genome-wide association studies (GWAS) data,
but that data can also be integrated with quantitative trait loci (eQTL or pQTL) information
to establish less obvious links between genetic variants (which often lie
outside of genes) and genes. Finally, there’s exome sequencing, which, unlike
GWAS, captures rare genetic variants. So in this paper, Marie and her
colleagues set out to benchmark these different methods against one another.
Listen to the episode to find out how these methods work, which ones
work better, and how network propagation can improve the prediction accuracy.

Links:
Multi-layered genetic approaches to identify approved drug targets
(Marie C. Sadler, Chiara Auwerx, Patrick Deelen, Zoltán Kutalik)

Marie on GitHub

Interview with Mariana Mamonova, the Ukrainian marine infantry combat medic who spent 6 months in russian captivity while pregnant

Thank you to Jake Yeung, Michael Weinstein, and other Patreon members for supporting this episode.
...more
53min
September 29, 2023#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 Optimal Compressed Space.
The suffix array is one of the foundational data structures in bioinformatics,
serving as an index that allows fast substring searches in a large text.
However, in its raw form, the suffix array occupies the space proportional to (and
several times larger than) the original text.
In their paper, Tomasz and Dominik construct a new index, δ-SA, which on the
one hand can be used in the same way (answer the same queries) as the suffix
array and the inverse suffix array, and on the other hand, occupies the space
roughly proportional to the gzip’ed text (or, more precisely, to the measure δ
that they define — hence the name).
Moreover, they mathematically prove that this index is optimal, in the sense
that any index that supports these queries — or even much weaker queries, such
as simply accessing the i-th character of the text — cannot be significantly
smaller (as a function of δ) than δ-SA.

Links:
Collapsing the Hierarchy of Compressed Data Structures: Suffix Arrays in Optimal Compressed Space (Dominik Kempa, Tomasz Kociumaka)

Thank you to Jake Yeung and other Patreon members for supporting this episode.
...more
57min
August 28, 2023#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 orthologous genes called OMA, Read2Tree bypasses traditional, time-consuming steps such as genome assembly, annotation and all-versus-all sequence comparisons.

Links:
Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree
(David Dylus, Adrian Altenhoff, Sina Majidian, Fritz J. Sedlazeck, Christophe Dessimoz)

Background story

Read2Tree on GitHub

OMA browser

The Guardian’s podcast about Victoria Amelina and Volodymyr Vakulenko

If you enjoyed this episode, please consider supporting the podcast on Patreon.
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50min
July 29, 2023#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 Copenhagen.
In the episode, Amelie explains what 𝛥𝛥G is, how it informs us
whether a particular protein mutation affects its stability, and how AlphaFold 2
helps in this analysis.

A note from Amelie:

Something that has happened in the meantime is the publication of methods
that predict 𝛥𝛥G with ML methods, so much faster than Rosetta. One of
them, RaSP, is from our group, while
ddMut is from another subset of
authors of the AF2 community assessment paper.
Other links:
A structural biology community assessment of AlphaFold2 applications
(Mehmet Akdel, Douglas E. V. Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O. Zalevsky, Bálint Mészáros, Patrick Bryant, Lydia L. Good, Roman A. Laskowski, Gabriele Pozzati, Aditi Shenoy, Wensi Zhu, Petras Kundrotas, Victoria Ruiz Serra, Carlos H. M. Rodrigues, Alistair S. Dunham, David Burke, Neera Borkakoti, Sameer Velankar, Adam Frost, Jérôme Basquin, Kresten Lindorff-Larsen, Alex Bateman, Andrey V. Kajava, Alfonso Valencia, Sergey Ovchinnikov, Janani Durairaj, David B. Ascher, Janet M. Thornton, Norman E. Davey, Amelie Stein, Arne Elofsson, Tristan I. Croll & Pedro Beltrao)

A crime in the making: Russia’s atrocities — the podcast episode about the Olenivka prison massacre

If you enjoyed this episode, please consider supporting the podcast on Patreon.
...more
36min
July 10, 2023#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.
Janani talks about how she used shape-mers and topic modelling to discover
classes of proteins assembled by AlphaFold 2 that were absent from the Protein
Data Bank (PDB).

The bioinformatics discussion starts at 03:35.
Links:
A structural biology community assessment of AlphaFold2 applications
(Mehmet Akdel, Douglas E. V. Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O. Zalevsky, Bálint Mészáros, Patrick Bryant, Lydia L. Good, Roman A. Laskowski, Gabriele Pozzati, Aditi Shenoy, Wensi Zhu, Petras Kundrotas, Victoria Ruiz Serra, Carlos H. M. Rodrigues, Alistair S. Dunham, David Burke, Neera Borkakoti, Sameer Velankar, Adam Frost, Jérôme Basquin, Kresten Lindorff-Larsen, Alex Bateman, Andrey V. Kajava, Alfonso Valencia, Sergey Ovchinnikov, Janani Durairaj, David B. Ascher, Janet M. Thornton, Norman E. Davey, Amelie Stein, Arne Elofsson, Tristan I. Croll & Pedro Beltrao)

The Protein Universe Atlas

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds (Janani Durairaj, Andrew M. Waterhouse, Toomas Mets, Tetiana Brodiazhenko, Minhal Abdullah, Gabriel Studer, Mehmet Akdel, Antonina Andreeva, Alex Bateman, Tanel Tenson, Vasili Hauryliuk, Torsten Schwede, Joana Pereira)

Geometricus: Protein Structures as Shape-mers derived from Moment Invariants on GitHub

The group page

The Folded Weekly newsletter

A New York Times article about the Kramatorsk missile strike. The Instagram video, part of which you can hear at the beginning of the episode, appears to have been deleted.

If you enjoyed this episode, please consider supporting the podcast on Patreon.
...more
21min
June 21, 2023#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 structure from its amino acid sequence.
Pedro is an associate professor at ETH Zurich and the coordinator of
the structural biology community assessment of AlphaFold2 applications project,
which involved over 30 scientists from different institutions.
Pedro talks about the origins of the project,
its main findings, the importance of the confidence metric that AlphaFold
assigns to its predictions, and Pedro’s own area of interest — predicting
pockets in proteins and protein-protein interactions.

Links:
A structural biology community assessment of AlphaFold2 applications
(Mehmet Akdel, Douglas E. V. Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O. Zalevsky, Bálint Mészáros, Patrick Bryant, Lydia L. Good, Roman A. Laskowski, Gabriele Pozzati, Aditi Shenoy, Wensi Zhu, Petras Kundrotas, Victoria Ruiz Serra, Carlos H. M. Rodrigues, Alistair S. Dunham, David Burke, Neera Borkakoti, Sameer Velankar, Adam Frost, Jérôme Basquin, Kresten Lindorff-Larsen, Alex Bateman, Andrey V. Kajava, Alfonso Valencia, Sergey Ovchinnikov, Janani Durairaj, David B. Ascher, Janet M. Thornton, Norman E. Davey, Amelie Stein, Arne Elofsson, Tristan I. Croll & Pedro Beltrao)

Pedro’s group at ETH Zurich

If you enjoyed this episode, please consider supporting the podcast on Patreon.
...more
53min
November 09, 2021#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 industry, specifically about how research
is conducted in the two settings. Then, they discuss the Enformer model,
how it builds on previous work, and the potential that models like it have
for genomics research in the future. Finally, they have a high-level discussion
on the state of modern deep learning libraries and which ones they use in their
day-to-day developing.

Links:
Effective gene expression prediction from sequence by integrating long-range interactions (Žiga Avsec, Vikram Agarwal, Daniel Visentin, Joseph R. Ledsam, Agnieszka Grabska-Barwinska, Kyle R. Taylor, Yannis Assael, John Jumper, Pushmeet Kohli & David R. Kelley )

DeepMind Blog Post (Žiga Avsec)

If you enjoyed this episode, please consider supporting the podcast on Patreon.
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1h
September 27, 2021#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 about how they approach
participating in the contest and what strategies have earned them the top
scores.

Timestamps and links for the individual problems:
00:10:36 Genotype Imputation

00:21:26 Causative Mutation

00:30:27 Superspreaders

00:37:22 Minor Haplotype

00:46:37 Isoform Matching
Links:
Matt’s solutions

Max’s solutions

If you enjoyed this episode, please consider supporting the podcast on Patreon.
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1h 1min
July 28, 2021#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 dingo, a
Python package written by Apostolos that employs geometric random walks to
sample steady states. You can see dingo in action
here.

Links:
Dingo on GitHub

Searching for COVID-19 treatments using metabolic networks

Tweag open source fellowships

This episode was originally published on the Compositional podcast.

If you enjoyed this episode, please consider supporting the podcast on Patreon.
...more
39min
June 23, 2021#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 talking about 3D genome structure at a high level
and the challenges in working with such data. Then, they discuss a method
recently developed by Erika, named GRiNCH, that mines this data to
identify spans of the genome that cluster together in 3D space and
potentially help control gene regulation.

Links:
GRiNCH: simultaneous smoothing and detection of topological units of genome organization from sparse chromatin contact count matrices with matrix factorization (Da-Inn Lee and Sushmita Roy)

GRiNCH Project Page

In silico prediction of high-resolution Hi-C interaction matrices (Shilu Zhang, Deborah Chasman, Sara Knaack, and Sushmita Roy)

If you enjoyed this episode, please consider supporting the podcast on Patreon.
...more
1h 10min

FAQs about the bioinformatics chat:

How many episodes does the bioinformatics chat have?

The podcast currently has 70 episodes available.

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