Christopher JF Cameron (he/him/his)

A blog post on REliable PIcking by Consensus (REPIC) is now live at @Nature Research Communities! REPIC reliably identifies #cryoEM particles with minimal input, and it’s free & #opensource! Read more here: go.nature.com/3YNf5d2 Explore REPIC on GitHub: github.com/ccameron/REPIC

This work was completed in collaboration with @SebSeager, Fred J Sigworth, Hemant D Tagare, and @MarkGerstein/@GersteinLab.

REPIC is publicly available on GitHub (licensed under the BSD-3 clause): github.com/ccameron/REPIC

REliable PIcking by Consensus (REPIC) is now published in @CommsBio 🎉 REPIC harnesses multiple #cryoEM particle pickers to improve #particlepicking, achieving expert-level results with minimal manual intervention. Check it out! doi.org/10.1038/s42003… #research

Congratulations to Art Palmer, whose election to the @theNASciences was just announced. This honor indicates the highest level of achievement and contribution to scientific research, as recognized by one’s peers: twitter.com/i/status/17853…

New Research: Posterior inference of Hi-C contact frequency through sampling frontiersin.org/articles/10.33… #Bioinformatics

Our team at #CZImagingInstitute is excited to share the #CryoET Data Portal beta release. With over 13,000 tomograms, it’s the start of what we hope will be a large, open-access portal of high-quality, standardized & annotated cryo-ET data. bit.ly/3T9sZ6D

REPIC (REliable PIcking by Consensus - github.com/ccameron/REPIC) is now available as a plugin for @scipion_em #cryoEM

This work was performed in collaboration with the Sigworth, Tagare, and Gerstein labs at Yale University.

REPIC uses graph theory and integer linear programming to find a set of high quality consensus particles from multiple picked particle sets. REPIC is publicly available on #github: github.com/ccameron/REPIC

Trouble choosing a #cryoEM particle picking algorithm for your protein of interest? Why choose one when you can use them all to get reliable picking! #ensembleLearning The REPIC (REliable PIcking by Consensus) preprint is now available on #bioRxiv: doi.org/10.1101/2023.0…

Excited to announce that "The EN-TEx resource of personal epigenomes & variant impact models" just came out: Cell.com/cell/fulltext/…. The paper represents the culmination of many years of work by >100 authors & has lots of useful information about allele-specific activity.

@GersteinLab @GersteinLab Thank you for the promotion of our work (with Profs. Hemant Tagare and Fred Sigworth). However, these abstract are poster submissions to #BPS2023 and represent ongoing work (manuscripts forthcoming). #CryoEM #MachineLearning

We're happy to announce that two new papers accepted in Biophysical Journal with @cjf_cameron & Prof. Hemant Tagare. Congratulations to the team! #cryoEM MIDLS - Membrane detection in cryo-EM using deep level sets ACCOORD - An ensemble methodology for cryo-EM particle picking

Great collaboration with @Schliekerlab. Congrats to Dr. @cjf_cameron!

In our final paper for 2022 Pei-Ling developed an elegant screening approach to close a major gap in our understanding of protein quality control: the identification of the machinery responsible for protein turnover in the mammalian nuclear envelope doi.org/10.1016/j.celr…

A fantastic series of YouTube videos for visually learning about transformers: Ep 0 - youtu.be/48gBPL7aHJY #DeepLearning #visualization

Excited to present at #ESHG2022 tonight on our new mitochondrial constraint model in Hall F1 @ 7.30pm. #mtDNA is such an important yet often overlooked part of our genome!

Not a wordle, just my PhD thesis committee’s availability ⬛️⬛️🟩⬛️⬛️ ⬛️⬛️⬛️🟩⬛️ ⬛️🟩⬛️⬛️🟩 🟩⬛️⬛️⬛️🟩 🟩⬛️⬛️🟩⬛️ ⬛️🟩🟩⬛️🟩

Congratulations to my former #UofG MSc student Matthew Kirchoff in the Kremer lab (@UofGComputing) on his recent #IEEE paper describing the prediction of chromosomal compartments from reference genomes using deep learning: 10.1109/BIBM52615.2021.9669521

After advising PhD & Master students for over a decade, there is one thing I find most students need to unlearn: the half-ass work mentality acquired during years of tests and homework. Let me explain (thread 🧵). 1/N #AcademicTwitter