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web-based command line interface  (DOE Systems Biology Knowledgebase)

 
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    DOE Systems Biology Knowledgebase web-based command line interface
    Web Based Command Line Interface, supplied by DOE Systems Biology Knowledgebase, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/command+line+interface+(cli)+to/web+based+command+line+interface/pmc04199484-53-22-28
    Average 90 stars, based on 1 article reviews
    web-based command line interface - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Likelihood-Based Gene Annotations for Gap Filling and Quality Assessment in Genome-Scale Metabolic Models
    Article Snippet: The workflow tools are fully integrated within the Department of Energy's System Biology Knowledgebase (KBase), and are publicly available via both a web-based command line interface (available at http://kbase.us ) and a web service API.



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    Image Search Results


    Patient journey for PGx testing workflow. During the pre-test consultation, patients provide informed consent, complete a PGx survey, and submit a DNA sample from a buccal swab. This sample undergoes DNA extraction and array genotyping, followed by bioinformatic analysis to characterize variants in selected PGx genes. Genotype calls are subsequently interpreted into metabolizer profiles and annotated with actionable recommendations from published guidelines. Finally, results are compiled into a PDF report, which is discussed with the patient during a post-test consultation.

    Journal: Frontiers in Pharmacology

    Article Title: Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

    doi: 10.3389/fphar.2024.1349203

    Figure Lengend Snippet: Patient journey for PGx testing workflow. During the pre-test consultation, patients provide informed consent, complete a PGx survey, and submit a DNA sample from a buccal swab. This sample undergoes DNA extraction and array genotyping, followed by bioinformatic analysis to characterize variants in selected PGx genes. Genotype calls are subsequently interpreted into metabolizer profiles and annotated with actionable recommendations from published guidelines. Finally, results are compiled into a PDF report, which is discussed with the patient during a post-test consultation.

    Article Snippet: For genotyping, idat files were converted to gtc format based on human genome build GRCh38. p13 using the Illumina Array Analysis Platform Genotyping Command Line Interface (iaap cli) (v1.1.0) followed by conversion to VCF using the python script gtc_to_vcf.py (v1.2.1) ( https://github.com/Illumina/GTCtoVCF ).

    Techniques: DNA Extraction

    Validation study design. (A) . DNA from a total of 73 unique reference cell lines were genotyped on the GSA chip to assess genotyping accuracy. Samples were selected due to the availability of well-characterized reference genotype calls (1KGP, GIAB) or reference calls for important PGx genes that have been validated experimentally by multiple labs (GeT-RM). (B) . Breakdown of samples by experiment. GIAB samples were ran in triplicate in a 3:1:1 design to enable measurement of inter- and intra-run reproducibility. Selected GeT-RM samples with known copy number variations (CNV) were also run across three runs to assess inter-run reproducibility of CNV calling.

    Journal: Frontiers in Pharmacology

    Article Title: Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

    doi: 10.3389/fphar.2024.1349203

    Figure Lengend Snippet: Validation study design. (A) . DNA from a total of 73 unique reference cell lines were genotyped on the GSA chip to assess genotyping accuracy. Samples were selected due to the availability of well-characterized reference genotype calls (1KGP, GIAB) or reference calls for important PGx genes that have been validated experimentally by multiple labs (GeT-RM). (B) . Breakdown of samples by experiment. GIAB samples were ran in triplicate in a 3:1:1 design to enable measurement of inter- and intra-run reproducibility. Selected GeT-RM samples with known copy number variations (CNV) were also run across three runs to assess inter-run reproducibility of CNV calling.

    Article Snippet: For genotyping, idat files were converted to gtc format based on human genome build GRCh38. p13 using the Illumina Array Analysis Platform Genotyping Command Line Interface (iaap cli) (v1.1.0) followed by conversion to VCF using the python script gtc_to_vcf.py (v1.2.1) ( https://github.com/Illumina/GTCtoVCF ).

    Techniques: Biomarker Discovery

    Genotyping concordance against 65 accuracy controls (per-site analysis). Heatmap showing concordance of 114 variants with true positives. 1KGP and GIAB samples were utilized as accuracy controls. Imputed sites have a lower callability compared to sites that are directly genotyped. TP (hom alt), True positive homozygous alternate; TN (het), true positive heterozygous; TN, True negative; FP, false positive; FN, false negative; NA, not in reference.

    Journal: Frontiers in Pharmacology

    Article Title: Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

    doi: 10.3389/fphar.2024.1349203

    Figure Lengend Snippet: Genotyping concordance against 65 accuracy controls (per-site analysis). Heatmap showing concordance of 114 variants with true positives. 1KGP and GIAB samples were utilized as accuracy controls. Imputed sites have a lower callability compared to sites that are directly genotyped. TP (hom alt), True positive homozygous alternate; TN (het), true positive heterozygous; TN, True negative; FP, false positive; FN, false negative; NA, not in reference.

    Article Snippet: For genotyping, idat files were converted to gtc format based on human genome build GRCh38. p13 using the Illumina Array Analysis Platform Genotyping Command Line Interface (iaap cli) (v1.1.0) followed by conversion to VCF using the python script gtc_to_vcf.py (v1.2.1) ( https://github.com/Illumina/GTCtoVCF ).

    Techniques:

    An example IPython startup script for Mamba .

    Journal: Journal of Synchrotron Radiation

    Article Title: Mamba : a systematic software solution for beamline experiments at HEPS

    doi: 10.1107/S1600577522002697

    Figure Lengend Snippet: An example IPython startup script for Mamba .

    Article Snippet: Since Bluesky recommends the IPython (Pérez & Granger, 2007 ) interactive command line interface (CLI) of Python for its regular use on beamlines, we designed Mamba with cooperation between the CLI ( Mamba backend) and our GUIs ( Mamba frontend) in mind; inspired by AutoCAD -like software (called ‘parametric modeling software’ in its industry), we extensively use what we call ‘command injection’ (Fig. 1 ) to implement this cooperation.

    Techniques: