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Journal Article
STCDB4ND: a signal transduction classification database for neurological diseases
Database, Volume 2025, 2025, baaf032, https://doi.org/10.1093/database/baaf032
Published: 02 May 2025
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The flowchart of the key factor recognition algorithm, in which M is the tr...
Published: 02 May 2025
Figure 1.
The flowchart of the key factor recognition algorithm, in which M is the transition matrix, R refers to the vector of node-ranks, d is damping factor, and ε is the iteration accuracy.
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The whole map of the the network of neurological diseases related cell sign...
Published: 02 May 2025
Figure 4.
The whole map of the the network of neurological diseases related cell signaling transduction pathways, and figures of heatmap generated from disease data collected from DiSignAtlas website and the PPI network of TUBA4A from NDAtlas website.
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Schematic diagram of the data processing and database structure of STCDB4ND...
Published: 02 May 2025
Figure 2.
Schematic diagram of the data processing and database structure of STCDB4ND in this study.
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How biological databases (DBs) implement the FAIR principles and promote FA...
Published: 25 April 2025
Figure 1.
How biological databases (DBs) implement the FAIR principles and promote FAIR data.
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Database (DB) stakeholders, their roles in data management, and how the edu...
Published: 25 April 2025
Figure 2.
Database (DB) stakeholders, their roles in data management, and how the educational curriculum will positively impact them.
Journal Article
A teaching and training framework to promote findable, accessible, interoperable, and reusable data generation in agriculture
Database, Volume 2025, 2025, baaf034, https://doi.org/10.1093/database/baaf034
Published: 25 April 2025
Journal Article
CPDMS: a database system for crop physiological disorder management
Database, Volume 2025, 2025, baaf031, https://doi.org/10.1093/database/baaf031
Published: 22 April 2025
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Collection of healthy and diseased plant images from various angles. (a). F...
Published: 22 April 2025
Figure 1.
Collection of healthy and diseased plant images from various angles. (a). Front view image (0°), (b) front view image (120°), (c) front view image (240°), (d) top view image, (e) petiole image (upper leaf), (f) petiole image (lower leaf).
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A snapshot of the CPDMS web database. The website is organized into an intr...
Published: 22 April 2025
Figure 2.
A snapshot of the CPDMS web database. The website is organized into an introduction and a physiological disorder collecting flow chart.
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Application of physiological disorder collecting images using a smartphone....
Published: 22 April 2025
Figure 3.
Application of physiological disorder collecting images using a smartphone. (a) Application main screen snap. (b) Major functions of application. (c) QR code-based management of object meta-information. (D) Upload of image. (E) My account includes user information and collected information such as i
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Plant disease symptom image annotation. (a) FW(Flower), (b) LF(Leaf), (c) T...
Published: 22 April 2025
Figure 4.
Plant disease symptom image annotation. (a) FW(Flower), (b) LF(Leaf), (c) TOP(Top view), (d) FR(Fruit), and (e) SV(Side view).
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Artificial intelligence training process.
Published: 22 April 2025
Figure 6.
Artificial intelligence training process.
Journal Article
Mapping assays to the key characteristics of carcinogens to support decision-making
Database, Volume 2025, 2025, baaf026, https://doi.org/10.1093/database/baaf026
Published: 22 April 2025
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Physiological disorder image database system. (a) Main screen interface of ...
Published: 22 April 2025
Figure 5.
Physiological disorder image database system. (a) Main screen interface of crop physiological disorder image management system (b) Crop stress and crop information included in the informational list category (c) Project creation list. (d) The database can be aligned in a list form of images taken by
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Correlation between Ralstonia solanacearum cell count and CP value...
Published: 22 April 2025
Figure 7.
Correlation between Ralstonia solanacearum cell count and CP value, and pathogen content in resistant and susceptible tomato tissues. (a) Correlation between the number of R. solanacearum (Bacterial Wilt pathogen) cells and CP value. (b) Measurement of Bacterial Wilt pathogen content in infected
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Proteins showing oxidative stress-dependent changes in localization. (a) In...
Published: 21 April 2025
Figure 2.
Proteins showing oxidative stress-dependent changes in localization. (a) In the Localizatome database, we identified 1910 proteins showing enhanced foci formation under oxidative stress. (b) Representative localization changes of stress granules and autophagy-related proteins. (c) Results of KEGG si
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Sequence features of oxidative stress-dependent localization change protein...
Published: 21 April 2025
Figure 3.
Sequence features of oxidative stress-dependent localization change proteins. (a) Motif analysis of proteins that show foci formation dependent on oxidative stress. (b) Representative localization changes of proteins with glutamic acid repeat motifs along with the disordered prediction score for eac
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Database content and construction of MIPD. (a) Data collection process in t...
Published: 21 April 2025
Figure 1.
Database content and construction of MIPD. (a) Data collection process in the MIPD. (b) Construction of MIPD. (c) User interface of the MIPD, supporting browsing, searching, and downloading of analysis results.
