@erencaneksi.bsky.social
PhD Student at Stein Aerts Lab of Computational Biology.
Reposted
We currently have a call for support that has gone out to European labs, to support FlyBase-UK. We are asking our colleagues from labs in the US and other countries to wait for a similar call to them that will go out in the near future, to support the US sites. We thank you for your patience.
URGENT: FlyBase has lost practically all its funding overnight; even user fees are tied up in denied grant funding. 🤬🤯
Any lab using @flybase.bsky.social please donate using the link in post below.
This incredible community, on whose backs our #Drosophila labs depend, can't be left out to dry.
Any lab using @flybase.bsky.social please donate using the link in post below.
This incredible community, on whose backs our #Drosophila labs depend, can't be left out to dry.
My lab studies bacterial infections. We spend a lot of time looking at (or for) species-specific genetic and genomic databases for hosts and microbes. FlyBase is the best of all—there is literally no comparison. Its existence is under threat. Please donate.
www.philanthropy.cam.ac.uk/give-to-camb...
www.philanthropy.cam.ac.uk/give-to-camb...
June 3, 2025 at 9:17 PM
We currently have a call for support that has gone out to European labs, to support FlyBase-UK. We are asking our colleagues from labs in the US and other countries to wait for a similar call to them that will go out in the near future, to support the US sites. We thank you for your patience.
Reposted
One thousand candidate enhancers tested in vivo in the mouse brain! A massive resource and oh so useful as validation set for genome-wide enhancer prediction methods. Super fun to be involved in one of the papers: ‘the prediction challenge paper’ by Nelson&Niklas et al www.cell.com/cell-genomic...
May 21, 2025 at 4:50 PM
One thousand candidate enhancers tested in vivo in the mouse brain! A massive resource and oh so useful as validation set for genome-wide enhancer prediction methods. Super fun to be involved in one of the papers: ‘the prediction challenge paper’ by Nelson&Niklas et al www.cell.com/cell-genomic...
Reposted
Check out our work on evaluating methods for predicting in vivo cell enhancer activity in the mouse cortex! Combined, scATAC peak specificity and sequence-based CREsted predictions gave the best predictive performance, aiming to advance genetic tool design for cell targeting in the brain.
Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex
Johansen et al. report the results of a community challenge to predict functional
enhancers targeting specific brain cell types. By comparing multi-omics machine learning
approaches using in vivo data...
www.cell.com
May 21, 2025 at 4:45 PM
Check out our work on evaluating methods for predicting in vivo cell enhancer activity in the mouse cortex! Combined, scATAC peak specificity and sequence-based CREsted predictions gave the best predictive performance, aiming to advance genetic tool design for cell targeting in the brain.
Reposted
We are looking for additional Group Leaders to join the growing computational biology community at VIB.
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
April 25, 2025 at 9:00 PM
We are looking for additional Group Leaders to join the growing computational biology community at VIB.
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
Reposted
Our new call for VIB.AI group leaders is online! Junior and senior positions available to develop innovative ML methods in biology. With professorship at CS or Medical Faculty. Deadline 14th June. DM for more info.
We are looking for additional Group Leaders to join the growing computational biology community at VIB.
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
If you are excited about combining AI and machine learning with fundamental biology, we would love to hear from you!
https://vib.ai/en/opportunities#/job-description/110906
April 26, 2025 at 11:00 AM
Our new call for VIB.AI group leaders is online! Junior and senior positions available to develop innovative ML methods in biology. With professorship at CS or Medical Faculty. Deadline 14th June. DM for more info.
Reposted
Very proud of two new preprints from the lab:
1) CREsted: to train sequence-to-function deep learning models on scATAC-seq atlases, and use them to decipher enhancer logic and design synthetic enhancers. This has been a wonderful lab-wide collaborative effort. www.biorxiv.org/content/10.1...
1) CREsted: to train sequence-to-function deep learning models on scATAC-seq atlases, and use them to decipher enhancer logic and design synthetic enhancers. This has been a wonderful lab-wide collaborative effort. www.biorxiv.org/content/10.1...
CREsted: modeling genomic and synthetic cell type-specific enhancers across tissues and species
Sequence-based deep learning models have become the state of the art for the analysis of the genomic regulatory code. Particularly for transcriptional enhancers, deep learning models excel at decipher...
www.biorxiv.org
April 4, 2025 at 9:04 AM
Very proud of two new preprints from the lab:
1) CREsted: to train sequence-to-function deep learning models on scATAC-seq atlases, and use them to decipher enhancer logic and design synthetic enhancers. This has been a wonderful lab-wide collaborative effort. www.biorxiv.org/content/10.1...
1) CREsted: to train sequence-to-function deep learning models on scATAC-seq atlases, and use them to decipher enhancer logic and design synthetic enhancers. This has been a wonderful lab-wide collaborative effort. www.biorxiv.org/content/10.1...
Reposted
Our new preprint is out! We optimized our open-source platform, HyDrop (v2), for scATAC sequencing and generated new atlases for the mouse cortex and Drosophila embryo with 607k cells. Now, we can train sequence-to-function models on data generated with HyDrop v2!
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
April 4, 2025 at 8:52 AM
Our new preprint is out! We optimized our open-source platform, HyDrop (v2), for scATAC sequencing and generated new atlases for the mouse cortex and Drosophila embryo with 607k cells. Now, we can train sequence-to-function models on data generated with HyDrop v2!
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
Reposted
We released our preprint on the CREsted package. CREsted allows for complete modeling of cell type-specific enhancer codes from scATAC-seq data. We demonstrate CREsted’s robust functionality in various species and tissues, and in vivo validate our findings: www.biorxiv.org/content/10.1...
April 3, 2025 at 2:30 PM
We released our preprint on the CREsted package. CREsted allows for complete modeling of cell type-specific enhancer codes from scATAC-seq data. We demonstrate CREsted’s robust functionality in various species and tissues, and in vivo validate our findings: www.biorxiv.org/content/10.1...
Reposted
This Fri Hongjie Li & Norbert Perrimon organize an FCA workshop at the Drosophila Research Conference. @erencaneksi.bsky.social from our lab talks presents the adult scATAC-seq atlas combined w/ whole-organism sequence-to-function models; and Bo Sun from (Li lab) presents a scATAC+ageing atlas!
March 19, 2025 at 6:32 PM
This Fri Hongjie Li & Norbert Perrimon organize an FCA workshop at the Drosophila Research Conference. @erencaneksi.bsky.social from our lab talks presents the adult scATAC-seq atlas combined w/ whole-organism sequence-to-function models; and Bo Sun from (Li lab) presents a scATAC+ageing atlas!
Reposted
ICYMI: Modelling and design of transcriptional enhancers
Modelling and design of transcriptional enhancers
Nature Reviews Bioengineering, Published online: 28 February 2025; doi:10.1038/s44222-025-00280-yEnhancers are genomic elements critical for regulating gene expression. In this Review, the authors discuss how sequence-to-function models can be used to…
www.nature.com
March 1, 2025 at 6:54 PM
ICYMI: Modelling and design of transcriptional enhancers
Reposted
We wrote a review article on modelling and design of transcriptional enhancers using sequence-to-function models.
From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design!
@natrevbioeng.bsky.social
www.nature.com/articles/s44...
From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design!
@natrevbioeng.bsky.social
www.nature.com/articles/s44...
Modelling and design of transcriptional enhancers - Nature Reviews Bioengineering
Enhancers are genomic elements critical for regulating gene expression. In this Review, the authors discuss how sequence-to-function models can be used to unravel the rules underlying enhancer activit...
www.nature.com
February 28, 2025 at 2:45 PM
We wrote a review article on modelling and design of transcriptional enhancers using sequence-to-function models.
From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design!
@natrevbioeng.bsky.social
www.nature.com/articles/s44...
From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design!
@natrevbioeng.bsky.social
www.nature.com/articles/s44...
Reposted
This has been a fantastic adventure - to capture the genomic regulatory code underlying brain cell types (using deep learning models trained on chromatin accessibility), and then use these models to compare cell types between the bird and mammalian brain
Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂
In a new study, Nikolai Hecker, Niklas Kempynck et al. in the team of @steinaerts.bsky.social explore 300 million years of brain evolution through the lens of enhancer codes.
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
February 14, 2025 at 12:06 PM
This has been a fantastic adventure - to capture the genomic regulatory code underlying brain cell types (using deep learning models trained on chromatin accessibility), and then use these models to compare cell types between the bird and mammalian brain
Reposted
Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂
In a new study, Nikolai Hecker, Niklas Kempynck et al. in the team of @steinaerts.bsky.social explore 300 million years of brain evolution through the lens of enhancer codes.
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium
Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We used deep learning to characterize these enhancer codes and devised three metr...
www.science.org
February 14, 2025 at 10:08 AM
Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂