Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph Bacterial Annotation, pass 2, blastp-based functional annotation (first pass)

https://github.com/ncbi/pgap.git

Path: bacterial_annot/wf_bacterial_annot_pass2.cwl

Branch/Commit ID: 02816f0d66e36c8eeba02d211cc90e36bf1c9df5

workflow graph scatter-wf3.cwl#main

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/scatter-wf3.cwl

Branch/Commit ID: 0b3846fbf866584870a0b1ce902b5574f549dfee

Packed ID: main

workflow graph workflow-pepinfo-backtranseq-cpgplot.cwl

https://github.com/ebi-wp/webservice-cwl.git

Path: workflows/workflow-pepinfo-backtranseq-cpgplot.cwl

Branch/Commit ID: b191ca3e4273b922bba6af4c1eacdaa86a5b62f4

workflow graph scatter-wf3.cwl#main

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/scatter-wf3.cwl

Branch/Commit ID: 4642316a30a95d4f3d135c18f98477886b160094

Packed ID: main

workflow graph trnascan_wnode and gpx_qdump combined

https://github.com/ncbi/pgap.git

Path: bacterial_trna/wf_scan_and_dump.cwl

Branch/Commit ID: 485f0be56cea77bff62b797ae7eff422a990a92c

workflow graph gp_makeblastdb

https://github.com/ncbi/pgap.git

Path: progs/gp_makeblastdb.cwl

Branch/Commit ID: bb2f26dfe630179737ec2ff08a8614f1f47abcaf

workflow graph chipseq-header.cwl

https://github.com/datirium/workflows.git

Path: metadata/chipseq-header.cwl

Branch/Commit ID: 17d4d046e72bce780c249150041efd16e7374992

workflow graph fastqPE2bam.cwl

https://github.com/ddbj/human-reseq.git

Path: Workflows/fastqPE2bam.cwl

Branch/Commit ID: a670d65837cc8f306096b5e5fde909192ba095ca

workflow graph count-lines5-wf.cwl

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/count-lines5-wf.cwl

Branch/Commit ID: cf9d7cdefa6dfb3b678636da02bc55b6108c04ac

workflow graph kallisto-demo.cwl

https://github.com/common-workflow-language/workflows.git

Path: workflows/kallisto-demo.cwl

Branch/Commit ID: 767d700e602805112a4c953d166e570cddfa2605