Cancer Systems Microscopy Lab, @UNSW. Imaging-based single cell systems biology mapping heterogeneity to understand cancer cell biology.

Joined December 2009
103 Photos and videos
Pinned Tweet
18 May 2025
Our #AI #research @NatureComms will help you use concepts from #multiomics data integration to fuse 4-channel imaging data into unlimitedly multiplexed image datasets to interrogate complex cell biology, like #EMT. rdcu.be/emtBc @UNSW @UNSWMedicine @vafaee_fatemeh

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11 Aug 2025
I've always loved the interface of art & science. @GarvanInstitute are doing this so well. It's such a great way to start a conversation & make the complexity of scientific image data appealing & accessible. Maybe @UNSWMedicine @artdesignunsw to up the ante? Science-Art Collab?
The Art of Discovery exhibition is now open! 11-22 Aug, 2-5pm @GarvanInstitute. Immerse yourself in a free illuminated art exhibition, or explore the gallery online & vote for your favourite. ow.ly/CjTj50WCFIb
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John Lock retweeted
11 Aug 2025
Replying to @felkohdigital
@felkohdigital wrote a beautiful popular science piece about how AI is advancing the inference of molecular function from analysis of cellular form, i.e. image-based phenotyping. If you want to explain your #HCS project to a friend, this might help! @unsw tinyurl.com/4ne8vcaj

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8 Aug 2025
Amazing to join the $25M National Breast Cancer Foundation @NBCF -funded AllClear team, fighting to find & treat dormant cancer cells, the 'seeds of relapse', hiding in bone & causing metastatic relapse in patients. @GarvanInstitute @UNSW @c_chaffer youtu.be/ERRbMx7JxLE?si=oIAZ…

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John Lock retweeted
Have $10M and want to cure some diseases? It costs ~$1B to invent a new medicine…but $10M buys you Project Encore, to see if ANY existing drug might be repurposed for ~100 diseases that have no treatments. Contact me - be a hero for desperate patients! docs.google.com/document/d/1…
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31 Jul 2025
Our #Extensible_Immunofluorescence (ExIF) technique is a bit like #AI doing #origami. From some starting information (raw images = sheets of paper), AI can re-fold many alternatives (virtual images = alternate origami), capturing more #single-cell biology. nature.com/articles/s41467-0…
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30 Jul 2025
New collab with & led by @KrisKilian showing brief capillary constriction drives cancer stem cell traits & tumorgenicity based on PIEZO mechanosensitivity. CTCs get an 'aggressiveness boost' from squeezing through small blood vessels. @UNSW @UNSWMedicine biorxiv.org/content/10.1101/…
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John Lock retweeted
18 May 2025
Our #AI #research @NatureComms will help you use concepts from #multiomics data integration to fuse 4-channel imaging data into unlimitedly multiplexed image datasets to interrogate complex cell biology, like #EMT. rdcu.be/emtBc @UNSW @UNSWMedicine @vafaee_fatemeh

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10 Oct 2024
Excited to share Cancer Systems Microscopy lab @UNSWMedicine multiplexed imaging (60 markers/cell) for #EMT research & #CTC phenotyping from #liquidbiopsy, extensible immunofluorescence (ExIF) for ♾️ computational multiplexing via routine 4-plex IF. tinyurl.com/36x7eu6w
10/15(火)14時~開催📣 「Nikon Asia Pacific Life Science Webinar」 【演題】Towards Precision Medicine with Systems Microscopy 【演者】Dr. John Lock @locusJ(ニューサウスウェールズ大学) ※本ウェビナーは英語講演です ▽お申込みはこちら events.zoom.us/ev/AilVvwFmO8… #Nikon #顕微鏡
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John Lock retweeted
In academia you sometimes have to work 7 days a week, but the freedom to choose which 7 days is unparalleled
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John Lock retweeted
Interested in applying Prophet for your own functional assay? Check out the manuscript biorxiv.org/content/10.1101/… or grab the model itself: github.com/theislab/prophet Really excited about this new predictive approach for phenotype & drug discovery, check it out!

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John Lock retweeted
Its flexible encoding allows Prophet to predict genetic perturbations, small molecules & treatment combinations within one model. It scales w data, improving as it learns. Interestingly, learning across phenotypes boosts results, like using IC50 or RNA data to infer morphology.
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John Lock retweeted
By leveraging transfer learning across various phenotypes, Prophet allows in silico prediction of unseen perturbations in unseen biological contexts to predict which experiments are more likely to succeed - reducing the number to perform by up to 60x in the IC_50 example below.
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John Lock retweeted
Thrilled to share our „PRedictor Of PHEnoTypes“ model Prophet! Led by @Alejandro__TL & @_yji_, Prophet is a transformer-based model that predicts outcomes for unseen experiments. It aims to understands biology by learning across assays and phenotypes over 4.7M experiments.
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John Lock retweeted
I'm excited to share the next version of patchwork with the world, available on CRAN now. First class support for gt tables and even more freedom with `free()` tidyverse.org/blog/2024/09/p…

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John Lock retweeted
REVIEW @NatImmunol @parkerlabPMCC The complexity of immune evasion mechanisms throughout the metastatic cascade nature.com/articles/s41590-0…
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John Lock retweeted
This important review from the @parkerlabPMCC has been published in @NatRevImmunol highlighting multiple mechanisms cancers use to evade immune detection during metastatic spread & considerations to target aggressive cancers @Nicole160368 @thomasbchadwick go.nature.com/4gq0URQ
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16 Sep 2024
When the @FT puts #OpenAccess in air quotes, we researchers who would prefer to spend public funds on research rather than private publisher's fees should realise that "Open Access" is the wrong solution to the right problem. We can do much better. ft.com/content/e91a9687-8373…
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17 Sep 2024
For those looking to invest in the #SpringerNatureIPO noted by @FT, please note the class action lawsuit filed against them and 5 other large academic journal publishers for contravention of Sherman Act anti-trust laws. lieffcabraser.com/antitrust/…

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