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Ragothaman Yennamalli Profile
Ragothaman Yennamalli

@StructBioinfo

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Sr. Asst Prof @SastraUniv | Bioinformatician, He/Him. co-organizer #YIM2024, Asso.Ed @csb_journal, Spl Issue Ed @BiophysJ Ed BMC Bioinformatics, Protein Science

India
Joined May 2013
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@StructBioinfo
Ragothaman Yennamalli
1 year
🚨🚨🚨Our latest work @SastraUniv got featured in.@NatureInd!!!🚨🚨🚨.@s_shricharan @SankarMaheshR @SubachandranJK.The work was funded by @ugc_india.
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@StructBioinfo
Ragothaman Yennamalli
4 hours
RT @PrinSciAdvOff: As part of the series of ongoing efforts to improve “Ease of Doing Science” in the country, yet another key milestone ch….
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@StructBioinfo
Ragothaman Yennamalli
9 hours
RT @KamounLab: Kudos Madhu @JMadhuprakash, Mau @mpcontreras4 and the whole team for this beautiful structure and study! 😍 #EffectorWisdom #….
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@StructBioinfo
Ragothaman Yennamalli
14 hours
Explore 3-D models in your browser, download PDB files. Dive in now: 🔗 #Proteomics #Metallomics #OpenData
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@StructBioinfo
Ragothaman Yennamalli
14 hours
🔬 New insight: our Deinococcus indicus DR1 atlas uncovers >100 previously uncharted proteins that may bind or move As, Cr, Co, Cu, Fe, Mn, Mo, Ni & Zn—hinting at a far-ranging metallome beyond the classic ars operon. ⚙️🧪 #Metallomics 4/5
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@StructBioinfo
Ragothaman Yennamalli
14 hours
Brief Stats: .📊 4128 proteins modelled with #AlphaFold.🔸 2145 structures at pLDDT ≥ 90.🔸 CATH / InterPro domains assigned to 2 735 sequences. 3/5.
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@StructBioinfo
Ragothaman Yennamalli
14 hours
This work is a long standing collaboration between Yennamalli Lab and Dr. Richa Priyadarshini’s group at Shiv Nadar University (@ShivNadarUniv). 2/5.
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@StructBioinfo
Ragothaman Yennamalli
14 hours
🚨🚨🚨.Yennamalli Lab is proud to announce a newly launched website: — a browsable, downloadable atlas of Deinococcus indicus DR1, the bacterium that shrugs off radiation ☢️ and arsenic 🧪. 1/5
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@StructBioinfo
Ragothaman Yennamalli
20 hours
RT @TheRealBuzz: Officially starting the countdown to the anniversary of #Apollo11 today. You may recall that a few months ago, India’s Spa….
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@StructBioinfo
Ragothaman Yennamalli
1 day
RT @Pavan_KumarGV: In 2 minutes, I try to explain what is scientific thinking. ft. Carl Sagan.
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@StructBioinfo
Ragothaman Yennamalli
3 days
RT @theoneamit: A every scientist/researcher/clinician should read this #book
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@StructBioinfo
Ragothaman Yennamalli
4 days
RT @khnh80044: This is brilliant 😂
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@StructBioinfo
Ragothaman Yennamalli
4 days
What a find today morning!. He Painted Bugs Like Jewels — And Changed Science Forever via @YouTube.
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@StructBioinfo
Ragothaman Yennamalli
5 days
RT @nitkal: Here's the online version of my talk at the BDBio symposium 2025 at IISc on "Decoding chromatin biology using Learning algorith….
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@StructBioinfo
Ragothaman Yennamalli
5 days
Call it the way this algorithm works, so far my TL has many saying good things about @ANRFIndia and their proposal submission system this time. This could be a good time to revisit this written by @_KarishmaK @poonam_thakur6 @MeghnaSrishti and myself.
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@StructBioinfo
Ragothaman Yennamalli
5 days
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@StructBioinfo
Ragothaman Yennamalli
5 days
This was an undergraduate research work by Aathi Manikandan!.
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@StructBioinfo
Ragothaman Yennamalli
5 days
The preprint is here 👉 If you’re working in enzyme discovery, biofuels, or structural ML, we’d love to hear your thoughts. Thanks for reading!.#LPMO #AlphaFold #Bioinformatics #MachineLearning #Biotech.
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@StructBioinfo
Ragothaman Yennamalli
5 days
This project started as a question:.Can few structural features alone tell us something useful about function?.Ofc—it can. And this approach might generalize to other enzyme families too. 9/10.
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@StructBioinfo
Ragothaman Yennamalli
5 days
What does this mean for biologists?.— You can functionally annotate LPMOs even with novel or borderline sequences.— You can use structure to discover or repurpose enzymes.— You get a clearer idea of why an LPMO behaves the way it does 8/10.
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@StructBioinfo
Ragothaman Yennamalli
5 days
With these features, we trained several ML models. 🥇 Best performer? SVM with an RBF kernel — 98% accuracy.🥈 MLP (tanh + adam) also did well — 97% accuracy.These models can classify LPMOs just from structural fingerprints! 7/10.
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