and you can grab it here : github.com/PhenoMe-Ecos...
November 5, 2026 at 9:12 AM
and you can grab it here : github.com/PhenoMe-Ecos...
Together we built a tool I feel very proud of, and I hope the bioimaging community finds it useful! 😊
try it out:
pip install phenome
or using @napari.org :
pip install phenome-gui
try it out:
pip install phenome
or using @napari.org :
pip install phenome-gui
November 4, 2026 at 12:06 AM
Together we built a tool I feel very proud of, and I hope the bioimaging community finds it useful! 😊
try it out:
pip install phenome
or using @napari.org :
pip install phenome-gui
try it out:
pip install phenome
or using @napari.org :
pip install phenome-gui
🚀Our latest work on AI embeddings and phenotyping is out! #PhenoMe is a new interactive tool bridging image representations derived from #FoundationModels with explainable features and biological readouts🕸️
www.biorxiv.org/content/10.6... Congrats to @aaitorg.bsky.social on this very exciting work!🥳
www.biorxiv.org/content/10.6... Congrats to @aaitorg.bsky.social on this very exciting work!🥳
November 4, 2026 at 4:49 PM
🚀Our latest work on AI embeddings and phenotyping is out! #PhenoMe is a new interactive tool bridging image representations derived from #FoundationModels with explainable features and biological readouts🕸️
www.biorxiv.org/content/10.6... Congrats to @aaitorg.bsky.social on this very exciting work!🥳
www.biorxiv.org/content/10.6... Congrats to @aaitorg.bsky.social on this very exciting work!🥳
PhenoMe #standards facilitate the integration of additional biological readouts into the image datasets, allowing a joint (multimodal😉) exploration and analysis
November 4, 2026 at 5:06 PM
PhenoMe #standards facilitate the integration of additional biological readouts into the image datasets, allowing a joint (multimodal😉) exploration and analysis
What if you could explore thousands of microscopy images as an interactive map, without training a single model? 🔬
I'm really excited to share our new framework and preprint:
"PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping" 🧵👇
I'm really excited to share our new framework and preprint:
"PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping" 🧵👇
November 4, 2026 at 12:06 AM
What if you could explore thousands of microscopy images as an interactive map, without training a single model? 🔬
I'm really excited to share our new framework and preprint:
"PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping" 🧵👇
I'm really excited to share our new framework and preprint:
"PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping" 🧵👇
★ PARLONS PEU...
★ PARLONS PEU - Socialisme libertaire
« C’est à la méthode expérimentale que nous devons les plus grandes découvertes scientifiques. Les philosophes de l’ancien temps, qui se basaient sur leur propre imagination pour expliquer les phénomè...
www.socialisme-libertaire.fr
November 4, 2026 at 4:55 PM
★ PARLONS PEU...
PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping https://www.biorxiv.org/content/10.64898/2026.10.29.762637v1
November 3, 2026 at 7:46 PM
PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping https://www.biorxiv.org/content/10.64898/2026.10.29.762637v1
Pretrained vision models (DINOv2, Cell-DINO, STED-FM) already capture rich visual patterns in microscopy images. Turning those embeddings into biological insight is still hard.
PhenoMe links them directly to your experimental metadata and classical morphological measurements.
PhenoMe links them directly to your experimental metadata and classical morphological measurements.
November 4, 2026 at 12:06 AM
Pretrained vision models (DINOv2, Cell-DINO, STED-FM) already capture rich visual patterns in microscopy images. Turning those embeddings into biological insight is still hard.
PhenoMe links them directly to your experimental metadata and classical morphological measurements.
PhenoMe links them directly to your experimental metadata and classical morphological measurements.
👌PhenoMe is model-agnostic, supporting the use of Foundation Models and representation learning in life sciences research. It integrates ready-to-use pretrained DINOv2 and STED-FM, and functionality to process images with any PyTorch model
November 4, 2026 at 5:24 PM
👌PhenoMe is model-agnostic, supporting the use of Foundation Models and representation learning in life sciences research. It integrates ready-to-use pretrained DINOv2 and STED-FM, and functionality to process images with any PyTorch model
#PhenoMe processes 🔬 images (2D, multichannel, time-lapse, with/without masks) with a pretrained vision model (e.g. DINOv2) and displays the latent space representation interactively (in Jupyter or Napari). This lets you explore new data acquisitions and identify existing phenotypes in a few clicks😎
November 4, 2026 at 5:02 PM
#PhenoMe processes 🔬 images (2D, multichannel, time-lapse, with/without masks) with a pretrained vision model (e.g. DINOv2) and displays the latent space representation interactively (in Jupyter or Napari). This lets you explore new data acquisitions and identify existing phenotypes in a few clicks😎
A fantastic book. Using the development of the first 6 Star Wars movies as the framework, Kaminsky has put together a fascinating exploration of Lucas‘ evolution as a creator, partner, father, and businessman. Recommended. www.goodreads.com/en/book/show...
The Secret History of Star Wars
Star Wars is one of the most important cultural phenome…
www.goodreads.com
November 1, 2026 at 10:26 PM
A fantastic book. Using the development of the first 6 Star Wars movies as the framework, Kaminsky has put together a fascinating exploration of Lucas‘ evolution as a creator, partner, father, and businessman. Recommended. www.goodreads.com/en/book/show...
LRCQ: phenome-wide heritability enrichment of genomic loci from GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763731v1
November 4, 2026 at 9:31 PM
LRCQ: phenome-wide heritability enrichment of genomic loci from GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763731v1
PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping https://www.biorxiv.org/content/10.64898/2026.10.29.762637v1
November 3, 2026 at 7:46 PM
PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping https://www.biorxiv.org/content/10.64898/2026.10.29.762637v1
LRCQ: phenome-wide heritability enrichment of genomic loci from GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763731v1
November 4, 2026 at 9:31 PM
LRCQ: phenome-wide heritability enrichment of genomic loci from GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763731v1
LRCP: identifying functionally related SNPs and genes from phenome-wide genetic-effect correlations using GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763742v1
November 4, 2026 at 5:31 PM
LRCP: identifying functionally related SNPs and genes from phenome-wide genetic-effect correlations using GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763742v1
LRCP: identifying functionally related SNPs and genes from phenome-wide genetic-effect correlations using GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763742v1
November 4, 2026 at 5:31 PM
LRCP: identifying functionally related SNPs and genes from phenome-wide genetic-effect correlations using GWAS summary statistics https://www.biorxiv.org/content/10.64898/2026.11.02.763742v1
Accelerometer-derived real-world sleep stages and risk of incident diseases: A UK Biobank cohort study and phenome-wide association analysis — by Jingsong Luo et al.
👉 https://tnyp.me/tKO2tkf2/s
👉 https://tnyp.me/tKO2tkf2/s
November 2, 2026 at 7:06 AM
Accelerometer-derived real-world sleep stages and risk of incident diseases: A UK Biobank cohort study and phenome-wide association analysis — by Jingsong Luo et al.
👉 https://tnyp.me/tKO2tkf2/s
👉 https://tnyp.me/tKO2tkf2/s
🔴 3D organoids successfully mimic native tissue architecture and hormone response.
🔥 "Living" disease models can now be biobanked directly from ectopic lesions.
🔗 academic.oup.com/molehr/artic...
🔥 "Living" disease models can now be biobanked directly from ectopic lesions.
🔗 academic.oup.com/molehr/artic...
WERF Endometriosis Phenome and Biobanking Harmonisation Project for Experimental Models in Endometriosis Research (EPHect-EM-Organoids): endometrial organoids as an emerging technology for endometrios...
Abstract. The aetiology of endometriosis remains poorly understood. In vitro model systems provide the opportunity to identify the mechanisms driving disea
academic.oup.com
November 5, 2026 at 12:07 PM
🔴 3D organoids successfully mimic native tissue architecture and hormone response.
🔥 "Living" disease models can now be biobanked directly from ectopic lesions.
🔗 academic.oup.com/molehr/artic...
🔥 "Living" disease models can now be biobanked directly from ectopic lesions.
🔗 academic.oup.com/molehr/artic...
QUANTUM Trails
Education event
🗓️ Sat, 7 Nov · 12:00 PM – 1:30 PM
📍 Science Gallery Bengaluru, Science Gallery, Bangalore
🎟️ Free
👥 Capacity 50
🎤 Manasi Narula, Srivikashini Krishnaraj
Education event
🗓️ Sat, 7 Nov · 12:00 PM – 1:30 PM
📍 Science Gallery Bengaluru, Science Gallery, Bangalore
🎟️ Free
👥 Capacity 50
🎤 Manasi Narula, Srivikashini Krishnaraj
QUANTUM Trails
Step beyond the visible and into the world of QUANTUM. Join our Mediators, Manasi and Srivikashini, as they trace the connections between science, art and imagination. Discover the stories and ideas behind the works and experience the many strange, playful and thought-provoking ways quantum phenome…
quantum.scigalleryblr.org
November 4, 2026 at 7:31 AM
QUANTUM Trails
Education event
🗓️ Sat, 7 Nov · 12:00 PM – 1:30 PM
📍 Science Gallery Bengaluru, Science Gallery, Bangalore
🎟️ Free
👥 Capacity 50
🎤 Manasi Narula, Srivikashini Krishnaraj
Education event
🗓️ Sat, 7 Nov · 12:00 PM – 1:30 PM
📍 Science Gallery Bengaluru, Science Gallery, Bangalore
🎟️ Free
👥 Capacity 50
🎤 Manasi Narula, Srivikashini Krishnaraj
📢 New publication 'Phenomic prediction I: Plot-level prediction of #lodging severity in #sorghum breeding trials using UAV-based photogrammetric height data' by Srinivasa Reddy Mothukuri et al. in The Plant Phenome Journal 🧪
doi.org/10.1002/ppj2...
doi.org/10.1002/ppj2...
Phenomic prediction I: Plot‐level prediction of lodging severity in sorghum breeding trials using UAV‐based photogrammetric height data
Lodging in sorghum (Sorghum bicolor (L.) Moench) presents a significant challenge for plant breeders due to the trade-off between lodging resistance and grain yield. Manually measuring lodging across...
doi.org
October 26, 2026 at 12:38 AM
📢 New publication 'Phenomic prediction I: Plot-level prediction of #lodging severity in #sorghum breeding trials using UAV-based photogrammetric height data' by Srinivasa Reddy Mothukuri et al. in The Plant Phenome Journal 🧪
doi.org/10.1002/ppj2...
doi.org/10.1002/ppj2...
Drug-repurposing analyses identified therapeutic targets and compounds, including established migraine treatments and candidates requiring experimental validation. Genetic correlations, Mendelian randomization, and a phenome-wide scan linked migraine liability to psychiatric, (🧵 5/7)
October 25, 2026 at 7:52 AM
Drug-repurposing analyses identified therapeutic targets and compounds, including established migraine treatments and candidates requiring experimental validation. Genetic correlations, Mendelian randomization, and a phenome-wide scan linked migraine liability to psychiatric, (🧵 5/7)
Phenome-wide map of 467k+ UK Biobank genomes highlights massive impact of structural variants (SVs) on human health:
🔹 37,063 SV-trait associations across 18k+ phenotypes & proteins
🔹 Rare SVs exert powerful effects on disease risk
🔹 82%+ of SVs hidden from prior copy-number studies
buff.ly/qFaqvuD
🔹 37,063 SV-trait associations across 18k+ phenotypes & proteins
🔹 Rare SVs exert powerful effects on disease risk
🔹 82%+ of SVs hidden from prior copy-number studies
buff.ly/qFaqvuD
October 22, 2026 at 5:00 AM
Phenome-wide map of 467k+ UK Biobank genomes highlights massive impact of structural variants (SVs) on human health:
🔹 37,063 SV-trait associations across 18k+ phenotypes & proteins
🔹 Rare SVs exert powerful effects on disease risk
🔹 82%+ of SVs hidden from prior copy-number studies
buff.ly/qFaqvuD
🔹 37,063 SV-trait associations across 18k+ phenotypes & proteins
🔹 Rare SVs exert powerful effects on disease risk
🔹 82%+ of SVs hidden from prior copy-number studies
buff.ly/qFaqvuD
Came across this article a couple of days ago and now am totally against the AI.
arxiv.org/abs/2602.19141
arxiv.org/abs/2602.19141
Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians
"AI psychosis" or "delusional spiraling" is an emerging phenomenon where AI chatbot users find themselves dangerously confident in outlandish beliefs after extended chatbot conversations. This phenome...
arxiv.org
October 19, 2026 at 4:17 PM
Came across this article a couple of days ago and now am totally against the AI.
arxiv.org/abs/2602.19141
arxiv.org/abs/2602.19141
Yet another shutout for the Stars! Phenome-Otter with 3 already :3
October 18, 2026 at 1:43 AM
Yet another shutout for the Stars! Phenome-Otter with 3 already :3