Automated Author ProfileGioiosa, Silvia
0000-0003-1302-8320
Gioiosa, Silvia
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.6 (sum of 15 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The folder "Homo_sapiens" contains 8 subfolders. Each of them is an individual input Bioproject downloaded from SRA and reanalized with the same transcriptomic pipeline in order to compute:1) Differentially Alternative spliced Genes (DAS) in .tsv format;2) Differentially expressed genes in csv format;3) Gene ontology analysis over DEGs results. When the analysis has produced statistically significant results for Gene Enrichment Ontology analysis, three .csv files have been added to each folder, one for BP=Biological Process results, one for CC=Cellular Component results and one for MF=Molecular Functions results.When a Bioprojects appears more than once, it means that DEGs have been computed over diffferent varibles (e.g. Rtt vs. wt) or treated as indipendent studies when multiple source materials are present. To distinguish the studies an "0", "1", "_2" progressive number has been added to the folder names (e.g. in PRJNA509687_0 the samples under study were iPSC derived neural cortical neurons RTT vs. Wt while in PRJNA509687_1 the samples were derived from iPSC derived neural progenitors RTT vs. Wt). To facilitate the folder navigation, a file named "parameters" has been added to each folder.4) DESeq2 inputs divided in:gene count matrices in csv formatassociated phenodata.csvThe same logic is applied to the main folder "Mus_musculus",which contains 13 subfolders with DAS and DEG results
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
The folder "Homo_sapiens" contains 8 subfolders. Each of them is an individual input Bioproject downloaded from SRA and reanalized with the same transcriptomic pipeline in order to compute:1) Differentially Alternative spliced Genes (DAS) in .tsv format;2) Differentially expressed genes in csv format;3) Gene ontology analysis over DEGs results. When the analysis has produced statistically significant results for Gene Enrichment Ontology analysis, three .csv files have been added to each folder, one for BP=Biological Process results, one for CC=Cellular Component results and one for MF=Molecular Functions results.When a Bioprojects appears more than once, it means that DEGs have been computed over diffferent varibles (e.g. Rtt vs. wt) or treated as indipendent studies when multiple source materials are present. To distinguish the studies an "0", "1", "_2" progressive number has been added to the folder names (e.g. in PRJNA509687_0 the samples under study were iPSC derived neural cortical neurons RTT vs. Wt while in PRJNA509687_1 the samples were derived from iPSC derived neural progenitors RTT vs. Wt). To facilitate the folder navigation, a file named "parameters" has been added to each folder.4) DESeq2 inputs divided in:gene count matrices in csv formatassociated phenodata.csvThe same logic is applied to the main folder "Mus_musculus",which contains 13 subfolders with DAS and DEG results
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
small-RNA seq analysis for article "Gene signatures in human granulosa cells from integrated analyses of multiple datasets"
Authors
- Dhori, Xhulio ;
- Gioiosa, Silvia ;
- Gonfloni, Stefania
Differential Splicing analysis for article "Gene signatures in human granulosa cells from integrated analyses of multiple datasets"
Authors
- Dhori, Xhulio ;
- Gioiosa, Silvia ;
- Gonfloni, Stefania
Differential Splicing analysis for article "Gene signatures in human granulosa cells from integrated analyses of multiple datasets"
Authors
- Dhori, Xhulio ;
- Gioiosa, Silvia ;
- Gonfloni, Stefania
test
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
The folder "Homo_sapiens" contains 8 subfolders. Each of them is an individual input Bioproject downloaded from SRA and reanalized with the same transcriptomic pipeline in order to compute:1) Differentially Alternative spliced Genes (DAS) in .tsv format;2) Differentially expressed genes in csv format;3) Gene ontology analysis over DEGs results. When the analysis has produced statistically significant results for Gene Enrichment Ontology analysis, three .csv files have been added to each folder, one for BP=Biological Process results, one for CC=Cellular Component results and one for MF=Molecular Functions results.When a Bioprojects appears more than once, it means that DEGs have been computed over diffferent varibles (e.g. Rtt vs. wt) or treated as indipendent studies when multiple source materials are present. To distinguish the studies an "0", "1", "_2" progressive number has been added to the folder names (e.g. in PRJNA509687_0 the samples under study were iPSC derived neural cortical neurons RTT vs. Wt while in PRJNA509687_1 the samples were derived from iPSC derived neural progenitors RTT vs. Wt). To facilitate the folder navigation, a file named "parameters" has been added to each folder.4) DESeq2 inputs divided in:gene count matrices in csv formatassociated phenodata.csvThe same logic is applied to the main folder "Mus_musculus",which contains 13 subfolders with DAS and DEG results.
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
test
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
test
Authors
- Gioiosa, Silvia ;
- Gasparini, Silvia ;
- Presutti, Carlo ;
- Rinaldi, Arianna ;
- Castrignanò, Tiziana ;
- Mannironi, Cecilia
small-RNA seq analysis for article "Gene signatures in human granulosa cells from integrated analyses of multiple datasets"
Authors
- Dhori, Xhulio ;
- Gioiosa, Silvia ;
- Gonfloni, Stefania