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In the EM-object paper, we seamlessly merged publicly available spatial transcriptomics data (10x Visium) with its corresponding H&E image, unlocking new insights from existing data! Ever wondered what insights could be extracted by integrating multiple data layers from your projects? This could provide a deeper understanding of what's going on in the tissue samples and impact drug discovery. Reach out if you want to discuss how to integrate multiomic data! https://lnkd.in/g4JdaFS8 #spatialtranscriptomics #multiomics #spatialbiology Enable Medicine

I’m pleased to announce that my newest scientific article published on Expert Systems with Applications during my Ph.D. in Informatics Engineering is already available online. This article addresses primary challenges that endure in the drug discovery field, including the multi-domain representation space of Drug-Target Interactions (DTIs), DTI understanding and model explainability, and the modeling of the pharmacological space based on information concerning binding pockets. This work presents a novel end-to-end binding-region-guided Transformer-based architecture that simultaneously predicts the 1D binding pocket and the binding affinity of DTI pairs, where the prediction of the 1D binding pocket guides and conditions the prediction of Drug-Target Affinity (DTA). Furthermore, it is capable of providing increasing DTI and prediction understanding due to the nature of the attention blocks and prediction of the 1D binding pocket. This work is the result of the effort performed by a scientific group composed of me and the following excellent researchers: Professor Joel P. Arrais and Professor José Luis Oliveira. https://lnkd.in/dTsra5kX

We’re thrilled to announce that our latest web tool Stain-iT™, developed in partnership with the Biosciences Division (BID) of Thermo Fisher Scientific has been awarded CiteAb’s Digital Science Tool of the Year 2024. Stain-iT enables researchers to plan and optimize their cell staining experiments. By selecting the preferred sample fixation status and choosing specific cellular structures to stain, researchers can preview how different dyes and probes will interact with their samples, helping ensuring their purchased products deliver optimal results in the lab. Launched as an MVP last April, its intuitive features and user-friendly interface have led to a growing fan-base amongst researchers worldwide. With more updates planned for later this year, the best of Stain-iT™ is yet to come! With this award-winning tool and our ongoing commitment to innovation, we continue to design and develop revolutionary digital science solutions to help empower scientists worldwide. For Research Use Only. Not for use in diagnostic procedures. #AwardWinning #Innovation https://lnkd.in/e_pv7zxG

"BioPhysical and Active Learning Screening (BioPALS), a rapid and versatile hit identification protocol combining AI-powered virtual screening with a confirmation workflow based on GCI and a suite of other orthogonal in vitro biophysical methods"...

#Podcast now available! Experts recently took part in a Podcast to discuss application of multiomics to novel target discovery in #immunooncology Eran Ophir (Chief Scientific Officer, Compugen) and Yaron Turpaz ירון טורפז (Senior Vice President and Senior Advisor, Data and Informatics Solutions, Compugen) discuss the advantages of using multi-omic and #computational approaches for the discovery of novel targets and mechanisms of action of novel drug candidates in immuno-oncology. Listen to the #podcast or read the transcript here to grow your knowledge, as we address questions including: ·    How are they applying multiomics to novel target discovery in the I–O space? ·    What advantages do multiomics approaches offer? What is the cutting edge currently in this space? ·    What is Compugen’s computational approach to developing its I–O pipeline? ·    The development of diagnostic and prognostic biomarkers remains a key challenge for the I–O space. How can computational approaches help in these efforts? Listen to the podcast or read the transcript here:

Continuous investment in technology talents is the way KFBIO promotes the development of digital pathology #KFBIO#Digitalpathology https://lnkd.in/gsxPERu6

#Technology #DataAnalytics #DataDriven Beyond AlphaFold: The Future Of LLM in Medicine: AlphaFold leaves a complex legacy: What will be the future of LLM in biology and medicine? Continue reading on Towards Data Science » #MachineLearning #ArtificialIntelligence #DataScience

Great course, with hands on practical and data-analytical workshops, as well as inspirational talks by invited scientists.

🥁 New preprint alert: #Benchmarking second-generation methods for cell-type #deconvolution of #transcriptomic data 👉 https://lnkd.in/diYZPWFW Second-generation #deconvolution methods can be trained with scRNA-seq data to estimate the cellular composition of bulk RNA-seq samples. This flexibility can unlock the deconvolution of any cell type, tissue, and organism, but poses major challenges to methods benchmarking. We put together a unique set of real and simulated datasets to comprehensively benchmark second-generation deconvolution tools in various scenarios, and systematically assess how deconvolution performance is affected by different sources of variation and bias. In addition, we provide the scientific community with an ecosystem of tools and resources, #omnideconv, that strongly simplifies the application, benchmarking, and optimization of deconvolution methods. 👉 omnideconv.org Great collaboration with Markus List ✨ 👏 Kudos to Alexander Dietrich and Lorenzo Merotto for leading this effort, and to all the co-authors: Konstantin P. Bernhard Eder Constantin Zackl Katharina Reinisch Edenhofer Frank Federico Marini Gregor Sturm 🙏 Many thanks to Universität Innsbruck #DiSC Austrian Science Fund FWF Oesterreichische Nationalbank Bundesministerium für Bildung und Forschung #MyeInfoBank for supporting our work We hope our study and set of tools and resources can be helpful to the scientific community 💫