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17 Research products

  • 2019-2023
  • Research data
  • Research software
  • Dataset
  • Digital Humanities and Cultural Heritage
  • Neuroinformatics

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Our dataset is focused on automatic voice recognition for the purpose of diagnosing language disorders; hence, our dataset consists of written documents. As a whole, our study dataset comprises of inquiries, assertive speech, and responses to all three. Young children are being asked these questions and taught these stories. Our focus is on children aged 0 to 6 years. We have polled numerous children within this age range with the permission of their families, including infants from our own family, extended family, neighbors, non-governmental organizations (NGOs) in Bangladesh who work with children, hospitals, and many more. The surveys focused mostly on eliciting responses from the children, whether via direct questioning or age-appropriate aggressive language. Any action or expression of approval in response to the question or statement counts as an answer. Children of varying ages reach several stages in their development of language. A baby who is 7-12 months old may utilize babbling consonant-vowel combinations and consonant sounds; a baby who is 12-20 months old may use gestures, identify their own name, etc. Prior to the experiment, we required to do an analysis of the dataset. Age, Speech in Bangla, Speech Translated in English, Response in Bangla, Response Translated in English, and label are the 6 columns that make up our dataset. We gathered information from kids as young as one month old and as old as sixty (60) months old. In addition, we can see that the number of normal samples is about twice as large as the number of impaired samples (out of 252 total samples. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Data; NARCI...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data; NARCIS
    Dataset . 2023
    License: CC BY
    Data sources: Datacite; NARCIS
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DANS-EASY
    Dataset . 2023
    Data sources: B2FIND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Data; NARCI...arrow_drop_down
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      Mendeley Data; NARCIS
      Dataset . 2023
      License: CC BY
      Data sources: Datacite; NARCIS
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DANS-EASY
      Dataset . 2023
      Data sources: B2FIND
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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file. 4. Meth_atlas output. Estimated cell and tissue proportions of contribution for all samples.

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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      figshare
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file. 5. Meth_atlas output. Estimated cell and tissue proportions of contribution for all samples.

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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file 7. List of DNase-seq data sets obtained from the ENCODE.

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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      figshare
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file 6. Differentially methylated regions (DMRs) in cfDNA of MTLE patients in comparison with controls.

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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: J. Hribar, Lawrence;

    Cross Key

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC 0
      Data sources: ZENODO
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    Authors: Kalm, Kristjan;

    fMRI data from participants performing a visual sequence recall task. The data is in BIDS 1.0.1 format but each participant's data is compressed into a single archive following a 'sub-*id*.tar.gz' pattern. For each participant there are three sub-folders: (1) 'anat' -- T1-weighted anatomical image. (2) 'func' -- (a) EPI BOLD images (multiband factor 2), (b) event timings data for contrast regressors (.tsv files). (3) 'fmap' -- EPI images in opposite phase-encoding direction to 'func' images to derive inhomogeneity field maps. For full details on the file formats included see the BIDS specification at https://bids-specification.readthedocs.io/en/stable/ The MRI data has been fully anonymised: all information linking the participants to the MRI scans has been removed. This included 'de-facing' where all facial features are removed from the images to ensure a greater degree of anonymity for data sharing purposes. De-facing was performed with 'pydeface' package (https://github.com/poldracklab/pydeface). The data was acquired at the Medical Research Council Cognition and Brain Sciences Unit (Cambridge, UK) on a 3T Siemens Prisma MRI scanner using a 32-channel head coil and simultaneous multi-slice data acquisition. Functional images were collected using 32 slices covering the whole brain (slice thickness 2 mm, in-plane resolution 2��2 mm) with acquisition time of 1.206 seconds, echo time of 30ms, and flip angle of 74 degrees. Each participant performed two scanning runs and 510 scans were acquired per run. The initial ten volumes from the run were discarded to allow for T1 equilibration effects. Stimulus presentation was controlled by PsychToolbox software: the trials were rear projected onto a translucent screen outside the bore of the magnet and viewed via a mirror system attached to the head coil. For full details of acquisition see 'Sequence learning recodes cortical representations instead of strengthening initial ones' by Kalm K, Norris D. PLOS Computational Biology, 2021. Analysis scripts for the data are available at: https://gitlab.com/kristjankalm/fmri_seq_ltm

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    Apollo
    Dataset
    License: CC BY NC SA
    Data sources: Apollo
    Apollo
    Dataset . 2021
    License: CC BY NC SA
    Data sources: Datacite
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      Apollo
      Dataset
      License: CC BY NC SA
      Data sources: Apollo
      Apollo
      Dataset . 2021
      License: CC BY NC SA
      Data sources: Datacite
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    Authors: Scientific Data Curation Team;

    This dataset contains key characteristics about the data described in the Data Descriptor The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

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    figshare
    Dataset . 2021
    License: CC 0
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    Dataset . 2021
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      Dataset . 2021
      License: CC 0
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    Authors: Team, Scientific Data Curation;

    This dataset contains key characteristics about the data described in the Data Descriptor The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

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    Dataset . 2021
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    Authors: Walton, Stephanie; Livermore, Laurence; Bánki, Olaf; Cubey, Robert; +10 Authors

    Tools and services evaluation speadsheet

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    ZENODO
    Dataset . 2020
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      ZENODO
      Dataset . 2020
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Our dataset is focused on automatic voice recognition for the purpose of diagnosing language disorders; hence, our dataset consists of written documents. As a whole, our study dataset comprises of inquiries, assertive speech, and responses to all three. Young children are being asked these questions and taught these stories. Our focus is on children aged 0 to 6 years. We have polled numerous children within this age range with the permission of their families, including infants from our own family, extended family, neighbors, non-governmental organizations (NGOs) in Bangladesh who work with children, hospitals, and many more. The surveys focused mostly on eliciting responses from the children, whether via direct questioning or age-appropriate aggressive language. Any action or expression of approval in response to the question or statement counts as an answer. Children of varying ages reach several stages in their development of language. A baby who is 7-12 months old may utilize babbling consonant-vowel combinations and consonant sounds; a baby who is 12-20 months old may use gestures, identify their own name, etc. Prior to the experiment, we required to do an analysis of the dataset. Age, Speech in Bangla, Speech Translated in English, Response in Bangla, Response Translated in English, and label are the 6 columns that make up our dataset. We gathered information from kids as young as one month old and as old as sixty (60) months old. In addition, we can see that the number of normal samples is about twice as large as the number of impaired samples (out of 252 total samples. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

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    Mendeley Data; NARCIS
    Dataset . 2023
    License: CC BY
    Data sources: Datacite; NARCIS
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    DANS-EASY
    Dataset . 2023
    Data sources: B2FIND
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      Mendeley Data; NARCIS
      Dataset . 2023
      License: CC BY
      Data sources: Datacite; NARCIS
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      Mendeley Data
      Dataset . 2023
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      Mendeley Data
      Dataset . 2023
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      DANS-EASY
      Dataset . 2023
      Data sources: B2FIND
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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file. 4. Meth_atlas output. Estimated cell and tissue proportions of contribution for all samples.

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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file. 5. Meth_atlas output. Estimated cell and tissue proportions of contribution for all samples.

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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file 7. List of DNase-seq data sets obtained from the ENCODE.

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    Authors: Martins-Ferreira, Ricardo; Leal, Bárbara; Chaves, João; Ciudad, Laura; +4 Authors

    Additional file 6. Differentially methylated regions (DMRs) in cfDNA of MTLE patients in comparison with controls.

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