Explore tweets tagged as #BioDataScience
Today we had our first #microbiome day🦠 at @HelmholtzMunich 🎉🎉🎉. Great talks, lots of inspiration and potential for collaboration💡.Big thanks to the organizers and everyone who enjoyed this day together with us. Stay tuned!📡.@CompHealthMuc @MunichDS @LMU_Muenchen
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🌐Join Viet Tran in Overcoming Statistical Challenges in Microbiome and Single Cell Research! 🏆🧪.📈Innovative Two-Stage Workflow:.1️⃣Hierarchical grouping of microbial or cell-type features.2️⃣Explicit handling of non-compositional covariates.#microbiome #singlecell #ISMBECCB2023
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Barplot of the number of job postings that contain mentions of specific #programming languages HT @BioDataScience #coding #python #java #rstats #javascript #compsci
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Red de grupos de investigación y entidades iberoamericanas (públicas y privadas) con el objetivo de afrontar los desafíos y oportunidades emergentes de la creciente fusión de innovación en los campos de la IA y BioData Science. #RiaBio #IA #BioDataScience #TICs #Iberoamérica
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Our lab @IEM_Augsburg in Universität Klinikum #Augsburg. We SAW where skin #microbiome data comes from, and now will think twice before "df.dropna()" any samples🙀. Big thanks to @amedeodetomassi for an amazing lab tour, Luise Rauer and their colleagues for making it possible😎👍
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Elevate your education with AI! 📚 And Unlock the power of AI! 🌐. #AIatIISER #DataScienceMasters #BioDataScience #HybridLearning #ProfessionalEducation #IISERTirupati #DigiatureTechnology
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In today's #JournalClub, we took a look at the compositional aspects of #microbiome data, and how to handle them during data analysis:. Moral of the story:
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🔬✨ Introducing MolE!.Join @Scietwas to witness MolE's empowering chemical compound #analysis 🌐🌟.⚙️ Molecular representation learned through embedding decorrelation.✨ Predicted growth-inhibitory effects against human gut pathogens. #ML #antimicrobial #resistance #ISMBECCB2023
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🔍Discover the power of PIMs (compositional power interaction models) in handling @HiTSeq data! 🧬.@JohannesOstner showcases PIMs' capabilities in DA testing with correlated features while respecting zero inflation and compositional constraints 📈🎯 #ISMBECCB2023
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Discover the power of #NetCoMi, the #R package disentangling microbial association #networks! 📊🔬. 🦠 Understand complex #microbial interactions.🌱 Statistical network estimation made easy.🔍 Unveil the differences between groups. Don't miss a showcase made by @stefpeschel ⭐
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🦠Unlocking Hierarchical Relationships in Viral #Metagenomic Data with #VirNest! 🧬.1️⃣ Virus gene-sharing network estimation by leveraging hierarchical protein association.2️⃣ Hierarchical partitions through nested stochastic block model.Join @DanielePugno in unveiling #microbiome
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📊 Unveiling Stable Interactions in High-Throughput data!.💡@StadlerMara introduce #robust #statistical workflow:.🔗 Application to interaction effects between chromatin modifications.🧬 Lasso model for hierarchical interactions.🔎 Stability-based model selection.#ISMBECCB2023
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🔬🌿 Reproducible #microbiome #dataanalysis with #QIIME2 🐍 #python!.🔍 q2-gglasso: Sparse microbial network estimation.📈 q2-classo: Sparse log-contrast regression and classification.Join @ovlasovets @microbiome_cosi to hear more about #openscience and #softwaredevelopment🚀💻
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