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Dataset results
11 results for “machine actionable”
The Machine-Actionable Ancient Text (MAAT) Corpus
<p>The Machine-Actionable Ancient Text (MAAT) Corpus is a new resource providing training and evaluation data for restoring lacunae in ancient Greek, Latin, and Coptic texts. Current text restoration systems require large amounts of data for training and task-relevant means for evaluation. The MAAT Corpus addresses this need by converting texts available in EpiDoc XML format into a machine-actionable format that preserves the most textually salient aspects needed for machine learning: the text itself, unclear letters, restorations, and lacunae. Structured test cases are generated from the corpus that align with the actual text restoration task performed by papyrologists and epigraphist, enabling more realistic evaluation than the synthetic tasks used previously. The initial 1.0 beta release contains approximately 134,000 text editions, 178,000 text blocks, and 750,000 individual restorations, with Greek and Latin predominating. This corpus aims to facilitate the development of computational methods to assist scholars in accurately restoring ancient texts.</p>
Light-activated molecular machines display broad spectrum antibacterial action
<p>TEM images of <em>E. coli</em> treated with 1% DMSO or 0.5x MIC of different visible light-activated molecular machines. Light-activated molecular machines (MM) are synthetic molecular structures that, following light activation, undergo successive unidirectional rotation that results in a drilling-like rapid motion that can thrust the motor through biological membranes. Transmission electron microscopy (TEM) images revealed that treatment of <em>E. coli</em> with 0.5x MIC of different MM (DL-654, DL-877, DL-878) followed by activation with 42.6 J cm<sup>-2</sup> of 405 nm light resulted in substantial changes in cell morphology including the detachment of the inner membrane from the cell wall, damage to peptidoglycan, distortion of the cell surface, and formation of outer membrane vesicles, denoting membrane and periplasmic stress, that were not evident in 1% DMSO-treated and irradiated cells. </p>
Data for Progress on Climate Action: a Multilingual Machine Learning Analysis of the Global Stocktake
<p>Data to go with our submission to Climatic Change titled "Progress on Climate Action: a Multilingual Machine Learning Analysis of the Global Stocktake".</p> <p>Dataset contains the embeddings (.zip with pickles) as well as the associated document items (idem), the most-closely associated keywords and paragraphs per topic in the final model (.xlsx), the reduced 2d embeddings with all selected paragraphs (.csv utf-8 encoded), as well as an overview with the meta-data per source (.csv utf-8 encoded).</p>
Machine-actionable data descriptions for Austria's digital landscape model
<p>The digital landscape model (DLM) is a compilation of several data sets that, among other things, form the data basis for official maps. It covers a variety of the 34 themes of the EU directive INSPIRE. The introduction of these themes enriched the metadata and made similar datasets easier to find. Unfortunately, the competent authority (BEV) only provides the associated data descriptions as a PDF export of an Excel spreadsheet without translations. This dataset contains the raw data and visualizations.</p>
Evaluation Data [Supplement to PhD "Machine-Actionable Assessment of Research Data Products"]
<p>This deposition consists of the raw data used for the evaluation chapter 6 of the dissertation "Machine-Actionable Assessment of Research Data Products" (Tobias Weber, yet unpublished).</p>
Shortcomings of Event-Based Metrics [Supplement to PhD "Machine-Actionable Assessment of Research Data Products"]
<p>This deposition includes a tabular overview of all publications analyzed by my PhD to identify and classify shortcomings of event-based metrics for research data products. The tabular overview is linked via its field "Key" to the bibtex file which holds the bibliographic information to replicate the results shown in the table.</p> <p>The deposition is supplementary material to the dissertation "Machine-Actionable Assessment of Research Data Products" (Tobias Weber, yet unpublished), especially chapter 3.</p>
Supplementary material 1 from: Penev L, Groom Q, Casino A, Barov B (2024) Uniting FAIR data through interlinked, machine-actionable infrastructures. Research Ideas and Outcomes 10: e126588. https://doi.org/10.3897/rio.10.e126588
Uniting FAIR data through interlinked, machine-actionable infrastructures
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules
GEO Series GSE129144. Mus musculus. 54 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules (RNA-Seq)
GEO Series GSE129143. Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing.
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules (ChIP-Seq)
GEO Series GSE129141. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Light-activated molecular machines are new mode-of-action, fast-acting broad-spectrum antibacterials that target the membrane
GEO Series GSE194286. Escherichia coli. 6 samples. Type: Expression profiling by high throughput sequencing.
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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.