Mitro Miihkinen

338 posts

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Mitro Miihkinen

Mitro Miihkinen

@mitroe

Computational Systems Biomedicine researcher at FIMM Passionate about data-driven biological discovery and finding treatments for diseases

Finland, Turku เข้าร่วม Nisan 2010
577 กำลังติดตาม263 ผู้ติดตาม
ทวีตที่ปักหมุด
Mitro Miihkinen
Mitro Miihkinen@mitroe·
Proper cell type annotation of #ST #SpatialTranscriptomics samples brings out even the most sophisticated tissue architectures of any tissue. Check out our latest open-source tools for this, now out in Bioinformatics: doi.org/10.1093/bioinf…
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Mitro Miihkinen@mitroe·
@MAG2ART Beautiful! What's the mitochondrion dye here? Asking for a friend😄
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Dylan Burnette
Dylan Burnette@MAG2ART·
Two cells photographed through a microscope. DNA in the nucleus and mitochondria in each cell are shown. #CellBiology
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Oliver Stegle
Oliver Stegle@OliverStegle·
Job alert! Joint us in Heidelberg to develop and apply computational methods to dissect molecular variation in CRC cancer. #Postdoc #SpatialOmics #MultiOmics #AI Apply here: embl.org/jobs/position/…
Stegle Lab@StatGenomics

We are looking for a postdoctoral researcher! Join our translational project aimed at exploring the processes that alter the epigenetic landscape of colorectal cancer cells and drive their metastasis. Become part of our group at @EMBL Apply here: embl.org/jobs/position/…

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Razvan Borza
Razvan Borza@rborza_·
🚨 Great alternatives to BioRender are now available!! 📢 @NIAIDNews offers a collection of public figures and icons for everyone to use. Check it out at bioart.niaid.nih.gov
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Itai Yanai
Itai Yanai@ItaiYanai·
If you think the next big idea in your field will come from inside the field, you're probably wrong.
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Oded Rechavi
Oded Rechavi@OdedRechavi·
Signing a PDF
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FIMM HelsinkiUni
FIMM HelsinkiUni@FIMM_UH·
Join FIMM as a MSCA Doctoral Researcher, to work in the field of multiplexed immunofluorescence profiling of cancer metastases. This fully funded 4-year position in Teijo Pellinen's team is part of the #Mac4Me network. Apply by Nov 22 👇 jobs.helsinki.fi/job/Helsinki-M… #sciencejobs
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FIMM HelsinkiUni
FIMM HelsinkiUni@FIMM_UH·
scTherapy, a novel machine learning approach from Tero Aittokallio and colleagues, leverages single-cell transcriptomic profiles to identify multi-targeting treatment options for individual patients with hematological cancers or solid tumors. helsinki.fi/en/hilife-hels…
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Colinda Scheele
Colinda Scheele@ColindaScheele·
👇🔬🧫Exciting story about human breast composition and 3D architecture in @CellReports: cell.com/cell-reports/f…👇Led by @oonakaroliina and Markus Peurla (@EPeuhu lab @BioscienceTurku ) with help of @kamyab_saberi and @larissamourao_ @vib_ccb @Onco_KULeuven
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Oona Paavolainen@oonakaroliina

🚨Publication alert! 🤝@EPeuhu I'm thrilled to announce that this project, the apple of my eye, is out! Here, we unveiled the 3D architecture and shed light on cellular complexity of healthy human breast tissue. I would love to tell you more about it🧵👇 :cell.com/cell-reports/f…

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Oliver Stegle
Oliver Stegle@OliverStegle·
Excited about multi-omics in health? We have a fully-funded PhD position on AI for multi-omics analytics as part of HIDDS4Health call 2024. Apply here: hidss4health.de
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FIMM HelsinkiUni
FIMM HelsinkiUni@FIMM_UH·
Researchers at FIMM have developed an effective computational platform that automatically identifies cell types from #SpatialTranscriptomics data. The method holds great potential for understanding tissue organisation in both health and disease. 💻⬇️ helsinki.fi/en/hilife-hels…
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Mitro Miihkinen
Mitro Miihkinen@mitroe·
@GorinGennady @lpachter Good call, did not remember it actually uses diffusion pseudotime to get pseudotime. Is it more robust for this reason? Maybe
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Lior Pachter
Lior Pachter@lpachter·
I have never seen a paper where the authors have formulated and experimentally tested a hypothesis based on a discovery made with RNA velocity. It's totally possible I have just missed this in the literature, and if so I'd love to see a reference. Thanks!
Lior Pachter@lpachter

This recently published figure by @Sarah_E_Ancheta et al. is very disturbing and should lead to some deep introspection in the single-cell genomics community (I doubt it will). It demonstrates complete disagreement among 5 widely used "RNA velocity" methods 1/

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