Project description:This is the fourth dataset for the new Chemical Standard to GNPS Library SOP workflow MSMS-Chooser Uploaded and run by the Dorrestein Lab.
Project description:This is the third dataset for the new Chemical Standard to GNPS Library SOP workflow MSMS-Chooser Uploaded and run by the Dorrestein Lab.
Project description:This is the sixth dataset for the new Chemical Standard to GNPS Library SOP workflow MSMS-Chooser Uploaded and run by the Dorrestein Lab.
Project description:This is the seventh dataset for the new Chemical Standard to GNPS Library SOP workflow MSMS-Chooser Uploaded and run by the Dorrestein Lab.
Project description:This is the second dataset for the new Chemical Standard to GNPS Library SOP workflow MSMS-Chooser Uploaded and run by the Dorrestein Lab.
These are the re-run samples from plate 2, after the instrument was fixed.
Project description:This is the second test dataset for the new Chemical Standard to GNPS Library SOP workflow. This data was collected when the instrument was in need of maintenance. Data was re-collected at a later date.
Project description:The MSMS-Chooser workflow enables the rapid data acquisition and analysis of chemical standards and uploads the MSMS spectra to the community-driven mass spectrometry platform GNPS. Tune methods, instrument methods, and test data generated from the Q Exactive for the MSMS-Chooser workflow can be found here.
Project description:Kinetic aqueous solubility (μg/mL) was experimentally determined using the same SOP in over 200 NCATS drug discovery projects. A final dataset of 11780 non-redundant molecules and their associated solubility was used to train a SVM classifier.
Model Type: Predictive machine learning model.
Model Relevance: Predicting the aqueous solubility of a chemical compound.
Model Encoded by: Pauline (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos74bo
Project description:Sonic hedgehog (Shh) signals via Gli transcription factors to stimulate proliferation of granule neuron precursor cells (GNPs) in the cerebellum. Deregulation of Shh target genes often results in unrestrained GNP proliferation and eventually medulloblastoma (MB), the most common pediatric brain malignancy. Gene expression profiling was coupled with transcription factor binding location analysis to determine the Gli1-controlled transcriptional regulatory networks in GNPs and medulloblastoma cells. We detected significant overlap, as well as differences, in the Gli1-controlled transcriptional regulatory networks in GNPs and MBs. We determined the presence of gene expression in each dataset. There were 9260 genes expressed in Gli1-FLAG GNPs and 9185 genes expressed in Gli1-FLAG;Ptc+/- tumors; 8691 of which are in common. The large overlap is consistent with the cellular origin of these tumors. When the genes detectably expressed were intersected with our binding data, there were only 132 putative Gli1 target genes shared by both cell populations. Due to the heightened activation of the Hh pathway in tumors relative to GNPs, we further deduced direct Gli1 target genes exclusive to tumors by determining significantly induced genes in tumors versus in Ptc+/- GNPs. We identified at least 116 tumor-specific Gli1 target genes. These data suggest that tumor formation is accompanied by a tremendous change in the battery of Gli target genes. Presence of gene expression was determined for all samples: Gli1-FLAG-expressing GNPs, Ptc+/- GNPs, and Gli1-FLAG;Ptc+/-medulloblastomas. These datasets were intersected with chIP-chip data to determine potential direct Gli1 target genes. Differential gene expression was determined by comparing expression profiles from medulloblastoma tumors to those from Ptc+/- GNPs.