Ricardo Hernández Medina
@ricardo_heme
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🎓 PhD Fellow @UCPH_CPR @CPHBiosciPhD 📚 Alumni @TNWTUDelft 🧬 Interested in deep learning, synthetic biology, and microbiomes 🏳️🌈 He/him
Copenhagen, Denmark
Joined October 2020
Why are you (as a microbial ecologist) missing out on #DeepLearning?. Check out our latest review article and learn how researchers leverage machine learning to interrogate the microbiome! 🦠🔍🖥️. Freely accessible in @ISMEComms:
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RT @RodericGuigo: Making our research available in local languages makes it accessible to the citizens funding it. It also prompts the deve….
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Today I presented my poster at @RECOMBconf ! It was fun to chat and exchange ideas with fellow researchers interested in multi-omics & deep learning, thanks for coming by!
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RT @Magda_Skipper: I've probably been the only person who's not shared views on ChatGPT in research writing on this platform; so here are s….
nature.com
Nature - As researchers dive into the brave new world of advanced AI chatbots, publishers need to acknowledge their legitimate uses and lay down clear guidelines to avoid abuse.
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RT @simonrasmu: Come join us (#PhD/#postdoc) in working on #precision #psychiatry using #bigdata #electronichealthrecords #EHR #machinelear….
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RT @TsangIngrid: SUPER EXCITED for the workshop and talks this afternoon with @JoVerran and @STSvienna 's Sarah Davies!!! Come join us in t….
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One last thing, I'm also excited to share that this is my first publication! 🥳 Many thanks to all co-authors for their valuable contribution and input during the writing process: @sveta_kutuzova, @NorNielsen, @JoJohanse, Lars H. Hansen, Mads Nielsen, and @simonrasmu!.
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But there's a catch 😅; there are a number of challenges in adopting these methodologies. ML is data-hungry 🫦 and (sometimes) works in mysterious ways 👽. Even so, we provide some tips and ideas to take into account if you wish to explore or exploit these novel methods. 🤓.
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Our article provides an overview of the strengths and applications of AI in microbiome research 💪. Examples include analyzing temporal patterns in longitudinal datasets ⏰ and revealing latent relationships between microbiome components ⛓️.
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All in all, it’s exciting to learn how new ML-based tools (like ionbot) are breaking the mold, and opening up new possibilities in LC-MS/MS data analysis! 🙌.
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Afterwards @RobbinBouwmees and Nina Demeulemeester walked us through their pipeline and shared some cool tricks along the way. With ionbot we can easily search for protein modifications 🔍, allowing us to follow up with a thorough differential expression analysis. 🤔
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Today we hosted an inspiring talk by Lennart Martens (@compomics):.New tools and perspectives are shaking the field of proteomics! It’s time to adapt to a new era. 💡.
An inspiring Snapshot talk from Lennart Martens @compomics today - exciting times for proteomics!. Thanks to @cphbiosciphd students including @MKoutrouli @CharuJain09 @ricardo_heme for excellent organizing and hosting.
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RT @A_Kurzyukova: @cphbiosciphd PhD students on the @UCPH_CPR CPR retreat in Skodsborg🇩🇰👩🏼🔬😍. @MariaMetelova @VKleinSousa @Freddyomics @ri….
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If you are interested in proteomics, post-translational modifications, and machine learning 🤓, join us for this talk and workshop at @UCPH_CPR!.
📢CPH Bioscience Snapshot on Sept 20! The Proteome, Version 2.0: Time to take PTMs (even more) seriously - talk by Lennart Martens @compomics + workshop🧬🤯👨💻. Organized by @cphbiosciphd students incl. @MKoutrouli @KabatnikSonja @CharuJain09 @ricardo_heme.
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RT @NinaRoothans: Do you want to discuss the intricacies of N2O producing/consuming communities and how we combine kinetics, metagenomics,….
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RT @TimmyPaez: Did you prepare for today’s conference at #ISME18 with a nice big breakfast? Microbes constantly store to prepare for the fu….
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