Pathway Tools version 24.0: Integrated Software for Pathway/Genome Informatics and Systems Biology

Karp, Peter D.; Paley, Suzanne M.; Midford, Peter E.; Krummenacker, Markus; Billington, Richard; Kothari, Anamika; Ong, Wai Kit; Subhraveti, Pallavi; Keseler, Ingrid M.; Caspi, Ron

doi:10.48550/arxiv.1510.03964

Cited by 8 publications

(6 citation statements)

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“…To allow broad access to tools to analyze the ASF, we have taken advantage of recent developments on https://www.BioCyc.org ( 54 ) and the downloadable Pathway Tools (PTools) software ( 55 , 56 ). Both environments support genome informatics (e.g., genome browser, sequence searching, multiple sequence alignment), pathway informatics (e.g., metabolic reconstruction, visualization of individual pathways and complete metabolic networks), comparative analysis (e.g., computation of orthologs and comparison of biosynthetic pathways across organisms) and ‘omics data analyses.…”

Section: Resultsmentioning

confidence: 99%

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

et al. 2022

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Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology.

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Section: Resultsmentioning

confidence: 99%

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

et al. 2022

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“…We further used the Pathway Tools software (Karp et al ., 2020) to generate PGDBs (Pathway Genome Databases) of the cancer-derived and non-cancer derived L. iners strains, in addition to a near complete assembly of a strain derived from a third patient’s WGS data, referred as I012T4 (97% completeness). Results of a comparative analysis of the generated PGDBs is provided in Supplementary tables (Supplemental table 5).…”

Section: Resultsmentioning

confidence: 99%

Cancer-associated Lactobacillus iners are genetically distinct and associated with chemoradiation resistance in cervical cancer

Colbert

Karpinets

Alam

et al. 2022

Preprint

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SUMMARYThis study identifies a novel pathotype of cervical cancer-associated Lactobacillus iners (L. iners) that results in chemoradiation resistance in vitro and is associated with poor patient survival. Cervical cancer affects over half a million women a year around the world. Treatment for women with locally advanced cancer is delivered with definitive chemoradiation (CRT) but is curative for only 60% of patients. There are few validated molecular markers to identify patients who will respond poorly to treatment. Tumor microbiome features are associated with treatment resistance in patients with colon and pancreatic cancers, and thus we investigated their role in the response of cervical cancer to therapy. We identified a strong association between poor clinical response to CRT and tumors dominated by L. iners. Cancer-associated L. iners promoted in vitro resistance of cervical cancer cells and modified the local tumor immunologic microenvironment, while non-cancer-associated L. iners did not. Assembly of genomes from cancer-derived L. iners also demonstrated pathogenic, metabolic, and immune functions not found in healthy patients.

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“…Both versions of the operon predictor obtain most input information (e.g., the organism’s genome, gene list, and proteome) from the Pathway/Genome Database (PGDB) describing the organism. The PGDBs are derived from RefSeq entries by the PathoLogic component of PTools [4]. The outputs of the operon predictor are written to the PGDB — each predicted operon is a PGDB object that specifies its component genes and includes a computational evidence code.…”

Section: Methodsmentioning

confidence: 99%

Improved BioCyc Operon Prediction: Revisiting the Operon Prediction Problem

Midford,

Cadigan,

Karp

2024

Preprint

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IntroductionOperon prediction is a valuable component of microbial-genome annotation because operon organization can yield inferences about gene function, and because knowledge of operon structure can aid the interpretation of gene expression data.MethodsWe present a number of improvements to the existing Pathway Tools operon predictor based mostly on 7 new features that we hypothesized would increase its performance. The new features include shared Gene Ontology biological process terms, similarity of codon usage and GC content, correlated gene expression, and shared protein complex.ResultsWe evaluated the proposed 7 new features and found that the addition of 6 of them improved the performance of the operon predictor from 79.55% to 83.49%, a decrease in error rate of 19.3%. When gene expression data was not included, the accuracy decreased to 82.547, still an improvement of 14.7%. One of the proposed features as well as a previously used feature had no effect and were removed.DiscussionAlthough some of the new features had strong predictive value individually, when combined with the other features they did not have a large impact on predictive accuracy, suggesting that they were not independent from the other features.

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Pathway Tools version 24.0: Integrated Software for Pathway/Genome Informatics and Systems Biology

Cited by 8 publications

References 0 publications

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

Cancer-associated Lactobacillus iners are genetically distinct and associated with chemoradiation resistance in cervical cancer

Improved BioCyc Operon Prediction: Revisiting the Operon Prediction Problem

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