Now available in PMC and Springer Nature's Scientific Data! Check out NCBI's publication, "Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets." https://ow.ly/vCgu50SxgiK #NCBICGR
National Center for Biotechnology Information (NCBI)’s Post
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Virtual and Augmented Reality, Data Science, Immersive Analytics, Visualization, Human-Computer Interaction, Computer Science
Good job on your first academic presentation 👍 ! Proud advisor moment. In this work, we looked at how different interaction methods can support the multi-focus data exploration of one-dimensional data (human genome data specifically). #ISMAR2023
Great experienced! Just finished the talk at IEEE ISMAR 2023 with the paper "Multi-Focus Querying of the Human Genome Information on Desktop and in Virtual Reality: an Evaluation." supervised under Yalong Yang and a great person to work with Gunnar Reiske! Link to the paper: https://lnkd.in/gidGFnGT Please have a look at the details: - Full Talk: https://lnkd.in/gg9_2TWT - Teaser: https://lnkd.in/g7v_GfG8
[IEEE ISMAR 23 - Full Talk] Multi-Focus Querying of the Human Genome Information
https://www.youtube.com/
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There is a small but growing number of examples of citizen science playing an active role in anticipatory action and early warnings. Can - and should - it play a greater role in the data used for anticipatory action? Read our latest blog here: https://lnkd.in/eNJGqRmS With ECSA - European Citizen Science Association and Practical Action. #CitizenScience #EarlyWarnings #AnticipatoryAction
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Camera trapping data on GBIF: Our three datasets are the first camera trap data shared on GBIF using the newly developed Camtrap DP (data exchange format for camera trap data) and the new publishing software package (version 3 of the Integrated Publishing Toolkit, #IPT) from GBIF. This extends the data publishing capabilities on GBIF beyond the Darwin Core Archive format to share data obtained from digital biodiversity sensors. Great to see on the GBIF platform all the occurrences together with the digital evidence (images) and all metadata of each data record in a machine- and human-readable #FAIR format! Thanks to Tim Robertson, Matthew Blissett and Mikhail Podolskiy (#GBIF), Peter Desmet (#INBO), Niels Raes and Jeroen Creuwels (#Naturalis, #NLBIF), Julian Evans (#UvA) and Yorick Liefting (#Agouti) for help with data storage and uploading, installation of the new software, and fixing various bugs. #ARISE #MAMBO #EuropaBON #Biodiversa+ #TABMON #LTERLIFE Dataset pilot 1: https://lnkd.in/e6A8SKkP Dataset pilot 2: https://lnkd.in/ekfe7qH4 Dataset pilot 3: https://lnkd.in/eJkUn_bS
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If you are wondering what I am up to these days, take a look at this recently published review on the interaction between GDF-15 and macrophages. @MDPIOpenAccess https://lnkd.in/eJF5ZkRQ
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When disasters occur, life-saving responses are necessary 🚑 🚁 Using a National Science Foundation (NSF) grant, our very own Dr. Mostafa Reisi Gahrooei will design a systematic data collection method that will help data agents collect reliable data under severe time and resource constraints! 🔗 bit.ly/3uNZ1LA
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Geospatial at HSSU
Harris-Stowe State University is leading the way for diversity in GEOINT by establishing Geospatial Science at HSSU. Learn more about HSSUs geospatial initiative here https://bit.ly/46UtQeY.
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🔎Today we dive into 7⃣ ways that data on alien species can be made more accessible, based on the results of a COST Association - European Cooperation in Science and Technology workshop 🪲 📰Explore the recommendations in this #PreviousResearch paper by Quentin Groom, Tim Adriaens, Peter Desmet, et al: https://lnkd.in/d3d5iHDC
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Our latest paper from the MLtox project is out today in Environmental Science: Advances, a great collaboration between Utox (Kristin Schirmer) and Siam (Marco Baity-Jesi) at Eawag and the Swiss Data Science Center (Lili Gasser and Fernando Perez-Cruz). We compare the performances of four state-of-the-art ML models with six molecular representations to predict acute ecotoxicity across 140 fish species from the ADORE t-F2F challenge dataset. https://lnkd.in/e6QumfJ6
Machine learning-based prediction of fish acute mortality: implementation, interpretation, and regulatory relevance
pubs.rsc.org
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Professor of River Science, drones for environmental monitoring, virtual fieldwork, Dept. of Geography at the University of Worcester
See below for free access to our newly published paper led by Salvatore Manfreda on "Advancing river monitoring using image-based techniques: Challenges and opportunities ".
Full Professor of Water Management, Hydrology and Hydraulic Constructions at the University of Naples Federico II and of the IAHS MOXXI working group.
🎉 Exciting News! 🎉 We are thrilled to announce that our community paper titled "Advancing river monitoring using image-based techniques: Challenges and opportunities" has just been published on #HSJ ! 📝 This significant milestone marks the culmination of extensive collaboration within the #MOXXI Working Group by IAHS - International Association of Hydrological Sciences. This paper would not have been possible without the generous support from research projects OurMED and #RiverWatch. Their contributions have been instrumental in bringing this important research to fruition. 🙌 The full paper is available at: https://lnkd.in/d-bwaywS 📚 #RiverMonitoring #Research #CommunityPaper #IAHS #MOXXI #Ourmed #Riverwatch
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Our past Conference Proceedings have been indexed in the Conference Proceedings Citation Index (CPCI) integrated within the Web of Science™ Core Collection. https://lnkd.in/g8d_7shz
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