Matches in Nanopublications for { ?s <http://schema.org/description> ?o ?g. }
- 974091bf-8775-46d4-b9d1-220b0c6811cc description "Subsampled descending orbit Cosmo-Skymed data of the Van earthquake" assertion.
- 9ca4b563-9c60-461c-969d-0424189b6c98 description "Data - Model - Residuals with InSAR descending data" assertion.
- a8c59911-6d74-4a15-9129-1c6320c9b74e description "VSM code - Research Object" assertion.
- ce25481c-812f-4dc5-8819-a015871495bc description "Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling - by E. Trasatti, C. Tolomei, G. Pezzo, S. Atzori, S. Salvi Rem. Sens., 2016. https://doi.org/10.3390/rs8060532" assertion.
- d6fd480f-eef3-427a-895e-871d7b4e5a48 description "Data - Model - Residuals with InSAR ENVISAT descending orbit" assertion.
- 532 description "Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling - by E. Trasatti, C. Tolomei, G. Pezzo, S. Atzori, S. Salvi Rem. Sens., 2016. https://doi.org/10.3390/rs8060532" assertion.
- 51daf908-532a-4e36-b7fc-9902de63f694 description "This Research Object has been created using the Reliance services. It aggregates results from the VSM run, related to the modelling of the coseismic deformation due to the Van earthquake (Turkey) of 23 October 2011. The geodetic dataset consists of InSAR slant and azimuth range measurements from COSMO-Skymed satellite, descending orbit ENVISAT data, and GNSS data. The forward model used is Okada (1985)." assertion.
- 531104de-d5d5-47bc-bca3-55b0a2c7c495 description "Data - Model - Residuals with InSAR azimuth direction" assertion.
- a74d0cde-ec98-4584-a7f4-4f7232d2c0af description "Data - Model - Residuals with InSAR descending data" assertion.
- efaec573-8bcf-490e-86ef-36b204e875c9 description "Data - Model - Residuals with InSAR ENVISAT descending orbit" assertion.
- content description "Jupyter Notebook for running the VSM code with geodetic data" assertion.
- 426b7f67a573ef34b110940437ed4ac9chbc69 description "VSM input file" assertion.
- 8988693c09e1d7207a952d39e3a70b23ch8dbe description "Subsampled descending orbit Cosmo-Skymed data of the Van earthquake" assertion.
- 980e8441348fd986f8f503148ea16838ch4b74 description "Subsampled azimuth direction Cosmo-Skymed data of the Van earthquake" assertion.
- ac4452cb8bc8b1dc987d83bd6939a246ch553a description "GNSS data of the Van earthquake" assertion.
- c6c4bc4e622ceb1cacee0b378e455338ch9b36 description "Subsampled descending orbit ENVISAR data of the Van earthquake" assertion.
- a25c47c7-f4dd-44d2-be2c-ab74b6a99070 description "This Research Object contains results from the run of the VSM code, related to the modelling of the inflation phase at Santorni during 2011-2012. The forward model is a spheroidal source arbitrary oriented in space. Input data are InSAR and GNSS data. This RO has been created using the Reliance services." assertion.
- d2ed7ad9-ce15-4cf8-80e8-0e2d6e9f443a description "Data - Model - Residuals with InSAR descending data" assertion.
- t83f-5t97 description "Research Object containing the details on the VSM Python tool" assertion.
- content description "Jupyter Notebook for running the VSM code with geodetic data" assertion.
- 260ca90cbcafbeb16566e4d2c29c6bf1chaf80 description "VSM input file" assertion.
- 49d62701a12530804aca9486cec01fe6ch33d0 description "GNSS data from 2011-2012 at Santorini (Greece)" assertion.
- dfdc97a96d6bc5322167aca4449a71d1ch6a9a description "Subsampled descending ENVISAT data from 2011-2012 at Santorini (Greece)" assertion.
- bf3d5a76-1be0-4221-8ee0-b3cb40faf6f7 description "Volcanic and Seismic source Modelling (VSM) is an open source Python tool to model ground deformation detected by satellite and terrestrial geodetic techniques. The VSM tool allows the user to choose one or more geometrical sources as forward model among sphere, spheroid, ellipsoid, fault, and sill. It supports multiple datasets from most satellite and terrestrial geodetic techniques: interferometric SAR, GNSS, levelling, Electro-optical Distance Measuring, tiltmeters and strainmeters. Two sampling algorithms are available, one is a global optimization algorithm based on the Voronoi cells and the second follows a probabilistic approach to parameters estimation based on the Bayes theorem. VSM can be executed as Python script, in Jupyter Notebook environments or by its Graphical User Interface. Version 1.0 April 2022. For any inquires, please write to elisa.trasatti@ingv.it" assertion.
- 8c18a91f-f196-4b0f-a95c-f6c290917747 description "License of use of VSM" assertion.
- ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef description "The research object refers to the Sea ice forecasting using IceNet notebook published in the Environmental Data Science book." assertion.
- b2a89d93-389e-4b18-8c66-c918d1826518 description "A demo given at the 3RD ESFRI-EOSC WORKSHOP ON RIS AND EOSC to show what the RELIANCE project has achieved on Open Science, FAIR and EOSC practice. Click on the links in the Research Object to access its different elements. The main resource of this Research Object is a video published on zenodo: https://doi.org/10.5281/zenodo.5906803" assertion.
- 54600d5f-9b3e-4b92-b399-df9226ec58c1 description "Folder where we will add links to documentation." assertion.
- b1e949bf-0514-4945-9fc9-8cbf89e96e4a description "Outputs generated" assertion.
- 62de154d-3a95-48f8-bd80-4e4f4b88f2a7 description "This figure shows all the services used within the RELIANCE project and how they are used together to build a user environment for Open Science and FAIR" assertion.
- ed4e6aa2-9db8-452d-9301-ba1606361034 description "NICEST-2 is the second phase of the Nordic Collaboration on e-Infrastructures for Earth System Modeling Tools and it focuses on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing initiatives. It builds on previous efforts within NICEST (a 3-year NeIC project as of 2017-01) and NordicESM (3-year NordForsk funded project from 2014-12). NICEST2 activities include: 1) Enhance the performance and optimize and homogenize workflows used, so climate models (like EC-EARTH and NorESM) can be run in an efficient way on future computing resources (like EuroHPC); 2) Widen the usage and expertise on evaluating Earth System Models and develop new diagnostic modules for the Nordic region within the ESMValTool; 3)Create a roadmap for FAIRification of Nordic climate model data." assertion.
- 4ed7f241-959a-41e5-bfb8-a4d53d3d1fa6 description "Initial Collaboration agreement for the NICEST2 project" assertion.
- 9ea437fd-1af0-4a1d-bc68-7af1c3bed34a description "Achievements of the NeIC NICEST2 project at the beginning of January 2022. This slide is part of a presentation that has been shown during the NeIC AHM22." assertion.
- a51d3ea3-89a6-443b-8d22-06f4c3ec71ee description "Business Case for the NICEST2 project." assertion.
- cc821096-f0f1-4a81-afd2-e311c899250c description "The submitted project proposal for the NICEST2 project." assertion.
- fd0ced6b-bfec-49bd-99b8-cb2db9f5c3f9 description "NICEST2 project plan. Please note that some changes may have been agreed during the course of the project." assertion.
- e919cbc4-2b0c-466a-a92f-9d5db1179301 description "NICEST-2 is the second phase of the Nordic Collaboration on e-Infrastructures for Earth System Modeling Tools and it focuses on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing initiatives. It builds on previous efforts within NICEST (a 3-year NeIC project as of 2017-01) and NordicESM (3-year NordForsk funded project from 2014-12). NICEST2 activities include: 1) Enhance the performance and optimize and homogenize workflows used, so climate models (like EC-EARTH and NorESM) can be run in an efficient way on future computing resources (like EuroHPC); 2) Widen the usage and expertise on evaluating Earth System Models and develop new diagnostic modules for the Nordic region within the ESMValTool; 3)Create a roadmap for FAIRification of Nordic climate model data." assertion.
- 3bcbf678-1c05-4939-8d41-880ef38061a6 description "NICEST2 project plan. Please note that some changes may have been agreed during the course of the project." assertion.
- 8f0ac9fc-f038-4bda-b57d-8460b422b88b description "Achievements of the NeIC NICEST2 project at the beginning of January 2022. This slide is part of a presentation that has been shown during the NeIC AHM22." assertion.
- 95b38dd2-7b6b-410e-9240-00636de7bfdb description "Business Case for the NICEST2 project." assertion.
- b993ee08-9d3a-42ea-b754-ae2ae805b3a2 description "Initial Collaboration agreement for the NICEST2 project" assertion.
- eb47d474-f350-4c3f-b543-e22ce008bd16 description "The submitted project proposal for the NICEST2 project." assertion.
- stable description "Link to the online JupyterLab documentation." assertion.
- stable description "Link to the online JupyterLab documentation." assertion.
- stable description "Link to the online JupyterLab documentation." assertion.
- docker-pangeo-notebook description "These docker images (different tags) correspond to the docker images built for Galaxy Pangeo JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-pangeo-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b" assertion.
- docker-pangeo-notebook description "This github repository contains all the sources required for building the docker containers that are made available in Quay Container Registry." assertion.
- tutorial.html description "Training material (hands-on) where Pangeo Notebook is used to learn Xarray. This training is part of the Galaxy Training Network (GTN). In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem. We will be using data from Copernicus Atmosphere Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. Parallel data analysis with Pangeo is not covered in this tutorial." assertion.
- 9c3bfd43-7e4f-4073-8735-f280ad4ab419 description "This Jupyter Docker container is used by the Galaxy Project. It is based on Pangeo notebook docker image (https://github.com/pangeo-data/pangeo-docker-images) and contained a few additional packages required for Galaxy (to exchange data, etc.)." assertion.
- 485cceaf-55f0-4915-944d-b1cbcccbd283 description "Default Jupyter Notebook used when starting Galaxy Climate JupyterLab if no other Jupyter Notebook is passed by the user." assertion.
- b2952190-8eb5-473c-be43-16eec919bfa2 description "This is a gif animated image showing how to start the Galaxy Pangeo JupyterLab in Galaxy Europe. In this video, we pass an input file (this file will be imported in the Jupyter Notebook /import folder)." assertion.
- cb076b25-1ae2-4b1d-8ed0-8875c5463e55 description "This is the Galaxy Pangeo JupyterLab tool wrapper used by Galaxy to start the Galaxy Pangeo JupyterLab on a Galaxy instance." assertion.
- f8b3510c-35aa-4492-89bb-b108b506749d description "Copernicus Atmosphere Monitoring Service PM2.5, 2 day forecasts, 24th December 2021 at 12:00 UTC" assertion.
- zenodo.5805953 description "Dataset used in the Galaxy Pangeo tutorials on Xarray. Data is in netCDF format and is from Copernicus Air Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. This dataset is very small and there is no need to parallelize our data analysis. Parallel data analysis with Pangeo is not covered in this tutorial and will make use of another dataset." assertion.
- zenodo.6399102 description "This is a tarball for the Docker Galaxy pangeo-JupyterLab image - Version 1c0f66b. To use it: download the image file docker-pangeo-notebook-1c0f66b.tar load it with docker with the command: docker load --input docker-pangeo-notebook-1c0f66b.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-pangeo-notebook for more details" assertion.
- climate-jupyter-galaxy_web.gif description "This is a gif animated image showing how to start the Galaxy Climate JupyterLab in Galaxy Europe" assertion.
- climate-jupyter-galaxy_web.gif description "This is a gif animated image showing how to start the Galaxy Climate JupyterLab in Galaxy Europe" assertion.
- map_vis_Galaxy.gif description "This is a gif animated image showing some of the functionalities of the Galaxy Climate JupyterLab" assertion.
- map_vis_Galaxy.gif description "This is a gif animated image showing some of the functionalities of the Galaxy Climate JupyterLab" assertion.
- cb869c7a-7a89-49dd-9038-b8a05a91dc6e description "🐳 🔬 📚 Jupyter running in a docker container. This image can be used to integrate Jupyter into Galaxy. This Jupyter Docker container is used by the Galaxy Project and can be installed from the quay.io index (https://quay.io/repository/nordicesmhub/docker-climate-notebook)." assertion.
- a5017748-4c4f-4546-b555-4b1323fce016 description "Default Jupyter Notebook used when starting Galaxy Climate JupyterLab if no other Jupyter Notebook is passed by the user." assertion.
- c8a9d642-c401-43c4-9436-58f866edb277 description "This is the Galaxy Climate JupyterLab tool wrapper used by Galaxy to start the Galaxy Climate JupyterLab on a Galaxy instance." assertion.
- f974c6a2-5fb5-45ae-b19f-03968d55060f description "Most of the resources and information of this Research Object were created from this Jupyter Notebook." assertion.
- zenodo.4543739 description "By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool, we are aiming at bridging the gap between climate scientists and non-climate specialists. Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational research. One of the strength of Galaxy is that it does not require programming experience and allow researchers to easily upload data, run complex tools and workflows in a reproducible manner, and visualize results. Galaxy Climate is quite new and aims at offering tools to everyone interested in Climate Science so that they can analyse and visualize climate data produced by climate scientists. However, climate scientists and in particular climate modellers have very different working practices: they often like to use command lines for running climate models and thanks to the PANGEO community (a community platform for Big Data geoscience) the Jupyter ecosystem has become very popular with several deployments of JupyterHubs dedicated to climate data analysis. By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool (https://live.usegalaxy.eu/?tool_id=interactive_tool_climate_notebook), we are aiming at bridging the gap between climate scientists and non-climate specialists. On this poster, we will show typical use cases both for research (https://nordicesmhub.github.io/eosc-nordic-climate-demonstrator/02-use-cases/) and for teaching (https://nordicesmhub.github.io/NEGI-Abisko-2019/intro)." assertion.
- zenodo.4543739 description "By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool, we are aiming at bridging the gap between climate scientists and non-climate specialists. Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational research. One of the strength of Galaxy is that it does not require programming experience and allow researchers to easily upload data, run complex tools and workflows in a reproducible manner, and visualize results. Galaxy Climate is quite new and aims at offering tools to everyone interested in Climate Science so that they can analyse and visualize climate data produced by climate scientists. However, climate scientists and in particular climate modellers have very different working practices: they often like to use command lines for running climate models and thanks to the PANGEO community (a community platform for Big Data geoscience) the Jupyter ecosystem has become very popular with several deployments of JupyterHubs dedicated to climate data analysis. By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool (https://live.usegalaxy.eu/?tool_id=interactive_tool_climate_notebook), we are aiming at bridging the gap between climate scientists and non-climate specialists. On this poster, we will show typical use cases both for research (https://nordicesmhub.github.io/eosc-nordic-climate-demonstrator/02-use-cases/) and for teaching (https://nordicesmhub.github.io/NEGI-Abisko-2019/intro)." assertion.
- zenodo.6394185 description "This is a tarball for the Docker climate-JupyterLab image - Version 2021-03-18. To use it: download the image file docker-climate-notebook-2021-03-18.tar load it with docker with the command: docker load --input docker-climate-notebook-2021-03-18.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-climate-notebook for more details" assertion.
- zenodo.6394185 description "This is a tarball for the Docker climate-JupyterLab image - Version 2021-03-18. To use it: download the image file docker-climate-notebook-2021-03-18.tar load it with docker with the command: docker load --input docker-climate-notebook-2021-03-18.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-climate-notebook for more details" assertion.
- docker-climate-notebook description "This github repository contains all the sources required for building the docker containers that are made available in Quay Container Registry." assertion.
- docker-climate-notebook description "This github repository contains all the sources required for building the docker containers that are made available in Quay Container Registry." assertion.
- docker-climate-notebook description "These docker images (different tags) correspond to the docker images built for Galaxy Climate JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-climate-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18" assertion.
- docker-climate-notebook description "These docker images (different tags) correspond to the docker images built for Galaxy Climate JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-climate-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18" assertion.
- 64aee73b-a05c-433f-bbf7-2ed35ec42601 description "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea" assertion.
- 47de04b7-3e7d-48ef-b79a-bee388d95a56 description "Satellite data on Chl-a and Kd490" assertion.
- 662ddab9-0d68-4808-b2de-6dcdda1adbd5 description "Results" assertion.
- 6a9dd591-fc94-41f6-b1c8-9a0498329c69 description "Discover, subset, download and visualize satellite data stored in a Data Cube from the ADAM Platform" assertion.
- 0bede41c-0982-459d-bf19-40125ce14de6 description "Discover and subset satellite data from the ADAM Platform" assertion.
- abe41c35-f2eb-411a-8fb0-d5eee9a27d7b description "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown" assertion.
- 15e9432f-53ee-4ea8-b1a3-6fdcaca7cf9e description "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea" assertion.
- 499ad5e0-87a2-4eb8-a4e9-4f36dde18085 description "Discover, subset, download and visualize satellite data stored in a Data Cube from the ADAM Platform" assertion.
- 7a81856f-ea74-465a-ad3c-9d45e39d7da4 description "Results" assertion.
- e46c4797-f9e9-409b-9ba9-12f6d88bd37b description "Satellite data on Chl-a and Kd490" assertion.
- 782bfaab-da7e-425a-ad09-51a01e156155 description "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown" assertion.
- 8cfd02af-82ac-46c7-af65-65f6f7e40f91 description "Discover and subset satellite data from the ADAM Platform" assertion.
- notebook.html description "Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book" assertion.
- 94486a7f-e046-461f-bbb9-334ec7b57040 description "The research object refers to the Tree crown delineation using detectreeRGB notebook published in the Environmental Data Science book." assertion.
- environment.yml description "Conda environment when user want to have the same libraries installed without concerns of package versions" assertion.
- notebook.ipynb description "Jupyter Notebook hosted by the Environmental Data Science Book" assertion.
- conda-linux-64.lock description "Lock conda file for linux-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book" assertion.
- conda-osx-64.lock description "Lock conda file for osx-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book" assertion.
- requirements.txt description "Pip requirements file containing libraries to install after conda lock" assertion.
- e05b90f7-5c22-4741-8b27-c43f5a5d70b4 description "This Research Object is related to the work on the coupling of the Norwegian Earth System Model with DIAM economic model to explore the economic impact of climate change." assertion.
- DIAM description "Private Github repository containing the source code for DIAM economic model." assertion.
- f55e746b-6a1e-4712-ac21-a3c99869783d description "🐳 🔬 📚 Jupyter running in a docker container. This image can be used to integrate Jupyter into Galaxy. This Jupyter Docker container is used by the Galaxy Project and can be installed from the quay.io index (https://quay.io/repository/nordicesmhub/docker-climate-notebook)." assertion.
- 1ed42fe1-b9ab-45aa-93fa-e4711e59ee46 description "This is the Galaxy Climate JupyterLab tool wrapper used by Galaxy to start the Galaxy Climate JupyterLab on a Galaxy instance." assertion.
- c478e527-cbca-4660-b2fa-cbfc9124b7d6 description "Most of the resources and information of this Research Object were created from this Jupyter Notebook." assertion.
- c54e557e-c1b7-4964-9989-9261fe5fd80c description "Default Jupyter Notebook used when starting Galaxy Climate JupyterLab if no other Jupyter Notebook is passed by the user." assertion.
- f84d00ef-47b2-40b3-af26-099ed7e82f5b description "<p>This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/ (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.</p>" assertion.
- 2ea2f7b6-1c15-454f-b62a-e7656bb81db4 description "This workflow lists all IDs and descriptions of the predefined concept set" assertion.
- 473e57ab-4056-427a-a8d9-b2c62e9b34d4 description "This workflow takes two concept ids as input and returns the top ranking "B" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group). This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/282 for functional gene and SNP annotation and knowledge discovery." assertion.
- 7f5b48a1-083d-4891-b311-b4627ceaa7ab description "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. "5" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services" assertion.
