Javascript must be enabled to continue!
GabiPD: Gabi Primary Database - a plant integrative ‘omics’ database in GABI-FUTURE
View through CrossRef
AbstractGabiPD ("http://gabi.rzpd.de":http://gabi.rzpd.de) was established within GABI-I and further developed in GABI-II and constitutes a repository and analysis platform for a wide array of heterogeneous data arising from high throughput experiments developed by members of the GABI/WPG community. Currently, data from different fronts (genomics, transcriptomics, proteomics, metabolomics) are incorporated in GabiPD, representing 14 different biological species. Last year GabiPD moved to the Max Planck Institute of Molecular Plant Physiology. In the progressing GABI-FUTURE phase, the GabiPD team has been creating a more integrative data view, expanding the tools and information provided by our well-known GreenCards. Links to different species-specific (Arabidopsis thaliana so far) GABI-resources (e.g., Aramemnon, GABI-KAT) as well as external resources (e.g., ProMEX) are being added or updated. All data types (e.g., protein spots, clones) in GabiPD are pointing to the central Gene’s GreenCard, where gene information is retrieved from genome annotation projects or large UniGene sets provided by NCBI. Moreover, the GabiPD team will perform new types of data computations, like analysis of conserved domains in protein sequences.
Springer Science and Business Media LLC
Title: GabiPD: Gabi Primary Database - a plant integrative ‘omics’ database in GABI-FUTURE
Description:
AbstractGabiPD ("http://gabi.
rzpd.
de":http://gabi.
rzpd.
de) was established within GABI-I and further developed in GABI-II and constitutes a repository and analysis platform for a wide array of heterogeneous data arising from high throughput experiments developed by members of the GABI/WPG community.
Currently, data from different fronts (genomics, transcriptomics, proteomics, metabolomics) are incorporated in GabiPD, representing 14 different biological species.
Last year GabiPD moved to the Max Planck Institute of Molecular Plant Physiology.
In the progressing GABI-FUTURE phase, the GabiPD team has been creating a more integrative data view, expanding the tools and information provided by our well-known GreenCards.
Links to different species-specific (Arabidopsis thaliana so far) GABI-resources (e.
g.
, Aramemnon, GABI-KAT) as well as external resources (e.
g.
, ProMEX) are being added or updated.
All data types (e.
g.
, protein spots, clones) in GabiPD are pointing to the central Gene’s GreenCard, where gene information is retrieved from genome annotation projects or large UniGene sets provided by NCBI.
Moreover, the GabiPD team will perform new types of data computations, like analysis of conserved domains in protein sequences.
Related Results
Benchmarking multi-omics integrative clustering methods for subtype identification in colorectal cancer
Benchmarking multi-omics integrative clustering methods for subtype identification in colorectal cancer
Abstract
Background and objectives
Colorectal cancer (CRC) represents a heterogeneous malignancy that has concerned global burden of incidence and mortality. The tradition...
Exploring the classification of cancer cell lines from multiple omic views
Exploring the classification of cancer cell lines from multiple omic views
Background
Cancer classification is of great importance to understanding its pathogenesis, making diagnosis and developing treatment. The accumulation of extensive o...
Multi-omics Data Integration by Generative Adversarial Network
Multi-omics Data Integration by Generative Adversarial Network
Accurate disease phenotype prediction plays an important role in the treatment of heterogeneous diseases like cancer in the era of precision medicine. With the advent of high throu...
Muon: multimodal omics analysis framework
Muon: multimodal omics analysis framework
AbstractAdvances in multi-omics technologies have led to an explosion of multimodal datasets to address questions ranging from basic biology to translation. While these rich data p...
A benchmark study of deep learning-based multi-omics data fusion methods for cancer
A benchmark study of deep learning-based multi-omics data fusion methods for cancer
Abstract
Background
A fused method using a combination of multi-omics data enables a comprehensive study of complex biological processes and highlig...
Topic Evolution Analysis for Omics Data Integration in Cancers
Topic Evolution Analysis for Omics Data Integration in Cancers
One of the vital challenges for cancer diseases is efficient biomarkers monitoring formation and development are limited. Omics data integration plays a crucial role in the mining ...
Multi-task learning from single-cell multimodal omics with Matilda
Multi-task learning from single-cell multimodal omics with Matilda
AbstractSingle-cell multimodal omics technologies enable multiple molecular programs to be simultaneously profiled at a global scale in individual cells, creating opportunities to ...
Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues
Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues
Abstract
Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant...

