Data files

columns are ' id' , 'ncbi_taxa_id' , 'common_names' , 'lineage_string' , 'genus' , 'species' , 'parent_id' , 'left_value' , 'right_value' , 'taxonomic_rank'.

columns are ' id' , 'ncbi_taxa_id' , 'common_names' , 'lineage_string' , 'genus' , 'species' , 'parent_id' , 'left_value' , 'right_value' , 'taxonomic_rank'.

columns are 'id' ,'name', 'term_type' , 'GOID', 'is_obsolete','is_root' and 'is_relation'

columns are ' id' , 'ncbi_taxa_id' , 'common_names' , 'lineage_string' , 'genus' , 'species' , 'parent_id' , 'left_value' , 'right_value' , 'taxonomic_rank'.

columns are 'id' ,'name', 'term_type' , 'GOID', 'is_obsolete','is_root' and 'is_relation'

Visualization of the workflow demonstrating a step-by-step explanation for a sc-SynO analysis. a) Several or one snRNA-Seq or scRNA-Seq fastq datasets can be used as an input. Here, we identify our cell population of interest and provide raw or normalized read counts of this specific population to sc-SynO for training. b) Further information for cluster annotation and processed count data are serving as input for the core algorithm. c) Based on the data input, we utilize the LoRAS synthetic ...

Validation of the sc-SynO model for the first use case of cardiac glial cell annotation. UMAP representation of the manually clustered Bl6 dataset of Wolfien et al. (2020) Precicted cells of sc-SynO are highlighted in blue, cells not chosen are grey. UMAP representation of the manually clustered dataset of Vidal (2019). Precicted cells of sc-SynO are highlighted in blue, cells not chosen are grey. Average expression of the respective top five cardiac glial cell marker genes for both validation ...

Validation of the sc-SynO model for the second use case of proliferative cardiomyocytes annotation. a) UMAP representation of the manually clustered single-nuclei dataset of Linscheid et al. (2019) Precicted cells of sc-SynO are highlighted in blue (based on top 20 selected features in the training model), red (based on top 100 selected features in the training model) cells not chosen are grey. b) UMAP representation of the manually clustered dataset of Vidal et al. (2020). PPrecicted cells of ...

The NFDI4Health Task Force COVID-19 Metadata Schema Mapping (Metadata Schema Mapping) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub) and how those properties align with other standards (FHIRE, CDISK, DRKS, ITRCP)

The NFDI4Health Task Force COVID-19 Metadata Schema (Metadata Schema) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub).

More information can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages/zebrafish

Source code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages/stickleback

There are four datasheets in the Excel file: 1. Gene pattern and the corresponding category (the gene list is then divided into the other three datasheets); 2. These gene names (patterns) can be directly followed by either a letter or a number; 3. These gene names (patterns) should be directly followed by a letter; 4. These gene names (patterns) should be directly followed by a number.

Biometric data from in vivo II experiment

The reactions existing in the auto-generated draft model are shown in blue, and the manually filled gaps are shown in green. Comparing our draft model with the same subsystem from model iHepatocytes2322, the missing reactions are highlighted in pink. The pink dots indicate the parent toxicants.

gadMorTrinity can be found at: https://doi.org/10.6084/m9.figshare.13067354.v1

COBRA Matlab toolbox was used.

Small set of values for entering into NetLogo simulation