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74 results for “Training school”
Twitter Poll: Is #OpenScience an essential rsrch skill Grad Schools should train in prep for #REF2020
<p>The Twitter Poll "Is #OpenScience an essential rsrch skill Grad Schools should train in prep for #REF2020" was run online in support of Horizon 2020 Project HEIRRI (Higher Education Insititutions & Responsible Research & Innovation) 1st Conference, 18 March 2016.</p> <p>The poll attracted 123 voters, 12,343 impressions and 517 engagements (4,2% conversion).</p> <p><em><strong>Event website:</strong></em><br /> HEIRRI 1st Conference http://heirri.eu/1st-heirri-conference/</p> <p><em><strong>CODE for EMBEDDING TWITTER POLL: </strong></em></p> <p><blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">Is <a href="https://twitter.com/hashtag/OpenScience?src=hash">#OpenScience</a> an essential rsrch skill Grad Schools should train in prep for <a href="https://twitter.com/hashtag/REF2020?src=hash">#REF2020</a> ? <a href="https://twitter.com/hashtag/OpenSci4Doc?src=hash">#OpenSci4Doc</a> <a href="https://twitter.com/HEIRRI_">@HEIRRI_</a></p>&mdash; Foster Open Science (@fosterscience) <a href="https://twitter.com/fosterscience/status/709650182800068608">March 15, 2016</a></blockquote><br /> <script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script></p>
PhasAGE Training School 2 - Phase separations and transitions by viral proteins: from viral factories to interference with host cell functions- LECTURE
<p>The Training School 2 “Biomolecular condensates in cell function, aging and disease” is the <strong>second</strong> edition of a series of PhasAGE training activities.</p> <p> </p> <p>The main goal of this training school is to raise awareness and provide expertise on fundamental aspects of phase separation and formation of <strong>biomolecular condensates</strong>, specifically covering the importance of this process to cellular biology and its contribution to the aging process and age-related diseases.</p>
PhasAGE Training School 2 - Condensation through liquid-liquid separation-LECTURE
<p>PhasAGE Training School 2 “Biomolecular condensates in cell function, aging and disease” is the<strong> second</strong> edition of a series of PhasAGE training activities.</p> <p>The main goal of this training school is to raise awareness and provide expertise on fundamental aspects of phase separation and formation of <strong>biomolecular condensates</strong>, specifically covering the importance of this process to cellular biology and its contribution to the aging process and age-related diseases.</p>
PhasAGE Training School 1 -Overview of bioinformatics tools for the life sciences & Classification and evolution of non-globular proteins- LECTUREs
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Computational prediction and databases of protein phase separation - PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Phase separation in diseases - LECTURE
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Computational prediction and databases of protein phase separation Overview- LECTURE
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Phase separation in virus-host interactions- LECTURE
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Structure and protein interactions of repeated and low complexity regions - LECTURE
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1-Protein aggregation prediction-PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Linear motifs identification and prediction - PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Computational prediction of intrinsic disorder in proteins-DisProt - PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Computational prediction of intrinsic disorder in proteins-MobiDB - PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
GNSS training - dataset - Wrocław - 1st GATHERS Summer School
<p>The files in the collection contain a 3D time-series of displacements in [m]. Data were collected before 1st GATHERS Summer School in Wrocław as a reference data. The observations were taken at the roof of Wrocław University of Environmental and Life Sciences - Institute of Geodesy and Geoinformatics: <a href="https://goo.gl/maps/W94mr2UhJKn7XH1z9">Location in Google Maps</a></p> <p>Please note that each file is containing 3 time-series in North, East and Up direction.</p> <p>There are three headers beginning each of the time-series.</p> <p>The GNSS_PPP.ascii contains the results of kinematic PPP (Precise Point Positioning)</p> <p>The GNSS_VAD.ascii contains the results of a kinematic variometric approach to GNSS data processing (from VADASE software).</p> <p>The ACC_DISPL.ascii contains the displacements calculated from accelerations measured with GeoTiny!AC accelerometer.</p> <p>The GNSS antenna and the accelerometer were co-located with a distance of 10 cm and rigidly connected.</p> <p>If some questions arise, please send a message to:</p> <p><a href="mailto:jan.kaplon@upwr.edu.pl">jan.kaplon@upwr.edu.pl</a>, </p> <p> </p>
GNSS training - dataset - Rybnik- 1st GATHERS Summer School
<p>The files in the collection contain a observation data, results and visualization algorithms. Data were collected during 1st GATHERS Summer School in Rybnik (<a href="https://www.kopalniaignacy.pl/en/">Ignacy Historic Mine</a>). The observations were taken at the Ignacy historical mine: <a href="https://goo.gl/maps/DEGFyDW5c3BfXDDR8">Location in Google Maps</a></p> <p>Following files are stored:</p> <p>GATHERS-T.5.1.1-Summer-School-GNSS-Observations-Results-PU.zip file contains following folders:</p> <p>- GNSS_data_Rybnik_2022-09-22 - RINEX files (GNSS receivers and smartphone) from field measurements (shaking table, bicycle wheel, base station) as well as GNSS products, for the day of measurements, required for GNSS data processing and used during the 1st Summer School GNSS training session,</p> <p>- Processing_Results_PPP_RTKLib - RTKLib PPP estimated 3D kinematic time-series of coordinates in IGb14 reference frame, shaking table results are only provided (GNSS receiver),<br> <br> - Processing_Results_variometric_VADASE - VADASE variometricaly estimated 3D kinematic time-series of coordinates in IGb14 reference frame, shaking table results are only provided (GNSS receiver),</p> <p>- Processing_Resuklts_Baseline_RTKLib - GNSS kinematic, baseline estimated 3D kinematic time-series of coordinates in IGb14 reference frame, shaking table results are only provided (GNSS receiver),</p> <p>- MINISEED_shaking_table_Rybnik_2022-09-22 - accelerometer data from shaking table experiment in MINISEED format, Warning due to accelerometer short power outages accelerometer time series are not time-aligned with GNSS results</p> <p>GNSSseismoRybnik_2022-09-22.ipynb - Google Colaboratory file containing the Python code used during the 1st Summer School GNSS training. The code loads GNSS processing results as well as accelerometer files into Python ObsPy seismological environment for data visualization and analysis. </p> <p>READ_ME_FIRST.txt - explanation of Google Colaboratory paths handling<br> <br> 20220922_143919.mp4, 20220922_145315.mp4, 20220922_145616.mp4 - the video files demonstrating of shaking table experiment </p> <p>If some questions arise, please send a message to:</p> <p><a href="mailto:jan.kaplon@upwr.edu.pl">jan.kaplon@upwr.edu.pl</a>, </p>
BL41XU experiment from the beamline training at CCP4 SPring-8 school 2018
<p>Raw X-ray diffraction images collected in the beamline training in day 2 of CCP4 SPring-8 school 2018 <a href="http://www.ccp4.ac.uk/schools/Japan-2018/program.php">http://www.ccp4.ac.uk/schools/Japan-2018/program.php</a></p> <p>On <strong>BL41XU</strong>, fine/coarse phi-slicing and radiation damage were demonstrated using thermolysin crystals. Datasets were collected using EIGER X 16M detector at 1.2824 Å wavelength. Beam size was 37.0 × 23.0 μm<sup>2</sup>. Here data from group 2 are available. See an Excel file for experimental conditions. Briefly, oscillation steps of 1° (data03) and 0.1° (data01) were tested under a total dose of 0.4 MGy, and radiation damage at 100 MGy (data02) and 10 MGy (data04) was demonstrated. You may also want to try phasing by Zn-SAD? For our EIGER data file format please look at <a href="https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md">https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md</a></p> <p> </p> <p>Other entries at CCP4 SPring-8 school 2018</p> <ul> <li>BL26B2 <a href="https://zenodo.org/record/1443392">https://zenodo.org/record/1443392</a></li> <li>BL32XU <a href="https://zenodo.org/record/1442922">https://zenodo.org/record/1442922</a></li> </ul>
BL32XU experiment from the beamline training at CCP4 SPring-8 school 2018
<p>Raw X-ray diffraction images collected in the beamline training in day 2 of CCP4 SPring-8 school 2018 <a href="http://www.ccp4.ac.uk/schools/Japan-2018/program.php">http://www.ccp4.ac.uk/schools/Japan-2018/program.php</a></p> <p>On <strong>BL32XU</strong>, the automatic data collection system ZOO was demonstrated using Br-lysozyme microcrystals. Multiple small-wedge (10 degrees per crystal) datasets were collected using EIGER X 9M detector at 0.9 Å wavelength. Beam size was 15.0 × 8.0 μm<sup>2</sup>. Here data from group 2 and group 3 are available (31 and 38 datasets, respectively). Due to the file size limitation, only hit images are uploaded for raster scan results. You may want to try merging and phasing by Br-SAD? For our EIGER data file format please look at <a href="https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md">https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md</a></p> <p> </p> <p>Other entries at CCP4 SPring-8 school 2018</p> <ul> <li>BL26B2 <a href="https://zenodo.org/record/1443392">https://zenodo.org/record/144339</a></li> <li>BL41XU <a href="https://zenodo.org/record/1443110">https://zenodo.org/record/1443110</a></li> </ul>
BL26B2 experiment from the beamline training at CCP4 SPring-8 school 2018
<p>Raw X-ray diffraction images collected in the beamline training in day 2 of CCP4 SPring-8 school 2018 <a href="http://www.ccp4.ac.uk/schools/Japan-2018/program.php">http://www.ccp4.ac.uk/schools/Japan-2018/program.php</a></p> <p>On <strong>BL26B2</strong>, strategy calculation was demonstrated using lysozyme crystals. Datasets and snapshots were collected using MX-225HS CCD detector at 1.0 and 1.5 Å wavelengths. Beam size was 120 μm (circle shape). All datasets collected in the course are available.</p> <p>Group1:</p> <ol> <li>Snapshot of cryo-cooled lysozyme crystal (well 2 of unipuck).<br> Discussion about data collection strategy. (Max. resolution, spot overlapping, exposure time etc.)</li> <li>Data collection of 360 images (./data1/*.img)<br> wavelength = 1 Å, exposure = 0.5 sec/ 0.5 deg, distance = 100 mm (edge resolution = 1.23 Å)</li> <li>Data processing with xdsgui.<br> Evaluation and discussion about data quality.</li> </ol> <p>Group2:</p> <ol> <li>Snapshot of cryo-cooled lysozyme crystal (well 3 of unipuck).<br> Discussion about data collection strategy. (Max. resolution, spot overlapping, exposure time etc.)</li> <li>Data collection strategy with imosflm and xdsgui, and discussion.</li> </ol> <p>Group3:</p> <ol> <li>Using snapshot of former group2, discussion about data collection strategy (especially for S-SAD)</li> <li>Data collection of 720 images (./data2/*.img); <br> wavelength = 1.5 Å, exposure = 0.5 sec/ 0.5 deg, distance = 100 mm (edge resolution = 1.85 Å)</li> <li>Data processing, S-SAD phasing, and model building with xdsgui.</li> </ol> <p> </p> <p>Other entries at CCP4 SPring-8 school 2018</p> <ul> <li>BL32XU <a href="https://zenodo.org/record/1442922">https://zenodo.org/record/1442922</a></li> <li>BL41XU <a href="https://zenodo.org/record/1443110">https://zenodo.org/record/1443110</a></li> </ul>
PhasAGE Training School 1 - Structure and protein interactions of repeated and low complexity regions - PRACTICAL
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
PhasAGE Training School 1 - Phase separation and emergent functions of Intrinsically Disordered Proteins- Lecture
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.