FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses

13C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13C-MFA software that works in various operating systems will enable more researchers to perform 13C-MFA and to further modify and develop the package.

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OpenMebius: An Open Source Software for Isotopically Nonstationary13C-Based Metabolic Flux Analysis

BioMed Research International ◽

10.1155/2014/627014 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 59

Author(s):

Shuichi Kajihata ◽

Chikara Furusawa ◽

Fumio Matsuda ◽

Hiroshi Shimizu

Keyword(s):

Open Source ◽

Open Source Software ◽

Metabolic Flux Analysis ◽

Metabolic Flux ◽

Simulated Data ◽

Isotopic Labeling ◽

Metabolic Model ◽

Cell Physiology ◽

Flux Analysis

Thein vivomeasurement of metabolic flux by13C-based metabolic flux analysis (13C-MFA) provides valuable information regarding cell physiology. Bioinformatics tools have been developed to estimate metabolic flux distributions from the results of tracer isotopic labeling experiments using a13C-labeled carbon source. Metabolic flux is determined by nonlinear fitting of a metabolic model to the isotopic labeling enrichment of intracellular metabolites measured by mass spectrometry. Whereas13C-MFA is conventionally performed under isotopically constant conditions, isotopically nonstationary13C metabolic flux analysis (INST-13C-MFA) has recently been developed for flux analysis of cells with photosynthetic activity and cells at a quasi-steady metabolic state (e.g., primary cells or microorganisms under stationary phase). Here, the development of a novel open source software for INST-13C-MFA on the Windows platform is reported. OpenMebius (Open source software for Metabolic flux analysis) provides the function of autogenerating metabolic models for simulating isotopic labeling enrichment from a user-defined configuration worksheet. Analysis using simulated data demonstrated the applicability of OpenMebius for INST-13C-MFA. Confidence intervals determined by INST-13C-MFA were less than those determined by conventional methods, indicating the potential of INST-13C-MFA for precise metabolic flux analysis. OpenMebius is the open source software for the general application of INST-13C-MFA.

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Open Plot Project: an open-source toolkit for 3-D structural data analysis

Solid Earth ◽

10.5194/se-2-53-2011 ◽

2011 ◽

Vol 2 (1) ◽

pp. 53-63 ◽

Cited By ~ 18

Author(s):

S. Tavani ◽

P. Arbues ◽

M. Snidero ◽

N. Carrera ◽

J. A. Muñoz

Keyword(s):

Spatial Distribution ◽

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Source Code ◽

Structural Data ◽

Geological Modelling ◽

Analysis Tools ◽

Transect Analysis ◽

Selection Of

Abstract. In this work we present the Open Plot Project, an open-source software for structural data analysis, including a 3-D environment. The software includes many classical functionalities of structural data analysis tools, like stereoplot, contouring, tensorial regression, scatterplots, histograms and transect analysis. In addition, efficient filtering tools are present allowing the selection of data according to their attributes, including spatial distribution and orientation. This first alpha release represents a stand-alone toolkit for structural data analysis. The presence of a 3-D environment with digitalising tools allows the integration of structural data with information extracted from georeferenced images to produce structurally validated dip domains. This, coupled with many import/export facilities, allows easy incorporation of structural analyses in workflows for 3-D geological modelling. Accordingly, Open Plot Project also candidates as a structural add-on for 3-D geological modelling software. The software (for both Windows and Linux O.S.), the User Manual, a set of example movies (complementary to the User Manual), and the source code are provided as Supplement. We intend the publication of the source code to set the foundation for free, public software that, hopefully, the structural geologists' community will use, modify, and implement. The creation of additional public controls/tools is strongly encouraged.

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In vivo 13C MRS in the mouse brain at 14.1 Tesla and metabolic flux quantification under infusion of [1,6-13C2]glucose

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x17734101 ◽

2017 ◽

Vol 38 (10) ◽

pp. 1701-1714 ◽

Cited By ~ 7

Author(s):

Marta Lai ◽

Bernard Lanz ◽

Carole Poitry-Yamate ◽

Jackeline F Romero ◽

Corina M Berset ◽

...

Keyword(s):

Mouse Brain ◽

Metabolic Flux ◽

Direct Detection ◽

Tricarboxylic Acid Cycle ◽

Quantitative Information ◽

Glutamine Metabolism ◽

Resonance Spectroscopy ◽

Flux Analysis ◽

Carboxylase Activity

In vivo 13C magnetic resonance spectroscopy (MRS) enables the investigation of cerebral metabolic compartmentation while, e.g. infusing 13C-labeled glucose. Metabolic flux analysis of 13C turnover previously yielded quantitative information of glutamate and glutamine metabolism in humans and rats, while the application to in vivo mouse brain remains exceedingly challenging. In the present study, 13C direct detection at 14.1 T provided highly resolved in vivo spectra of the mouse brain while infusing [1,6-13C2]glucose for up to 5 h. 13C incorporation to glutamate and glutamine C4, C3, and C2 and aspartate C3 were detected dynamically and fitted to a two-compartment model: flux estimation of neuron-glial metabolism included tricarboxylic acid cycle (TCA) flux in astrocytes (Vg = 0.16 ± 0.03 µmol/g/min) and neurons (VTCAn = 0.56 ± 0.03 µmol/g/min), pyruvate carboxylase activity (VPC = 0.041 ± 0.003 µmol/g/min) and neurotransmission rate (VNT = 0.084 ± 0.008 µmol/g/min), resulting in a cerebral metabolic rate of glucose (CMRglc) of 0.38 ± 0.02 µmol/g/min, in excellent agreement with that determined with concomitant 18F-fluorodeoxyglucose positron emission tomography (18FDG PET).We conclude that modeling of neuron-glial metabolism in vivo is accessible in the mouse brain from 13C direct detection with an unprecedented spatial resolution under [1,6-13C2]glucose infusion.

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Metabolic control of nitrogen fixation in rhizobium-legume symbioses

Science Advances ◽

10.1126/sciadv.abh2433 ◽

2021 ◽

Vol 7 (31) ◽

pp. eabh2433

Author(s):

Carolin C. M. Schulte ◽

Khushboo Borah ◽

Rachel M. Wheatley ◽

Jason J. Terpolilli ◽

Gerhard Saalbach ◽

...

Keyword(s):

Metabolic Flux ◽

Tricarboxylic Acid Cycle ◽

Oxygen Demand ◽

Metabolic Model ◽

Redox Balance ◽

Ammonia Assimilation ◽

Nodule Formation ◽

Flux Analysis ◽

Carbon And Nitrogen ◽

Genome Scale

Rhizobia induce nodule formation on legume roots and differentiate into bacteroids, which catabolize plant-derived dicarboxylates to reduce atmospheric N2 into ammonia. Despite the agricultural importance of this symbiosis, the mechanisms that govern carbon and nitrogen allocation in bacteroids and promote ammonia secretion to the plant are largely unknown. Using a metabolic model derived from genome-scale datasets, we show that carbon polymer synthesis and alanine secretion by bacteroids facilitate redox balance in microaerobic nodules. Catabolism of dicarboxylates induces not only a higher oxygen demand but also a higher NADH/NAD+ ratio than sugars. Modeling and 13C metabolic flux analysis indicate that oxygen limitation restricts the decarboxylating arm of the tricarboxylic acid cycle, which limits ammonia assimilation into glutamate. By tightly controlling oxygen supply and providing dicarboxylates as the energy and electron source donors for N2 fixation, legumes promote ammonia secretion by bacteroids. This is a defining feature of rhizobium-legume symbioses.

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Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

10.2196/preprints.32745 ◽

2021 ◽

Author(s):

Fabian Kovacs ◽

Max Thonagel ◽

Marion Ludwig ◽

Alexander Albrecht ◽

Manuel Hegner ◽

...

Keyword(s):

Decision Making ◽

Big Data ◽

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Medical Records ◽

Healthcare Sector ◽

Study Cohort ◽

Decision Making Processes ◽

Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

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Development of Assessment Criteria for Various Open Sources GIS Software Packages

Research Anthology on Usage and Development of Open Source Software ◽

10.4018/978-1-7998-9158-1.ch022 ◽

2021 ◽

pp. 398-412

Author(s):

Shahriar Shams

Keyword(s):

Open Source ◽

Open Source Software ◽

Assessment Criteria ◽

Significant Development ◽

Analysis And Design ◽

Advantages And Disadvantages ◽

Software Packages ◽

Open Source Gis ◽

Gis Software

There has been a significant development in the area of free and open source geospatial software. Research has flourished over the decades from vendor-dependent software to open source software where researchers are paying increasing attention to maximize the value of their data. It is often a difficult task to choose particular open source GIS (OGIS) software among a number of emerging OGIS software. It is important to characterise the projects according to some unified criteria. Each software has certain advantages and disadvantages and it is always time consuming to identify exactly which software to select for a specific purpose. This chapter focuses on the assessment criteria enabling developers, researchers, and GIS users to select suitable OGIS software to meet their requirements for analysis and design of geospatial application in multidisciplinary fields. This chapter highlights the importance of assessment criteria, followed by an explanation of each criteria and their significance with examples from existing OGIS software.

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Bayesian metabolic flux analysis reveals intracellular flux couplings

Bioinformatics ◽

10.1093/bioinformatics/btz315 ◽

2019 ◽

Vol 35 (14) ◽

pp. i548-i557 ◽

Cited By ~ 3

Author(s):

Markus Heinonen ◽

Maria Osmala ◽

Henrik Mannerström ◽

Janne Wallenius ◽

Samuel Kaski ◽

...

Keyword(s):

Steady State ◽

Metabolic Flux Analysis ◽

Metabolic Flux ◽

Reaction Network ◽

Reaction Rates ◽

Supplementary Information ◽

Flux Analysis ◽

Metabolic Reaction ◽

Metabolic Systems ◽

Genome Scale

AbstractMotivationMetabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.ResultsWe introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.Availability and implementationThe COBRA compatible software is available at github.com/markusheinonen/bamfa.Supplementary informationSupplementary data are available at Bioinformatics online.

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Takin: An open-source software for experiment planning, visualisation, and data analysis

SoftwareX ◽

10.1016/j.softx.2016.06.002 ◽

2016 ◽

Vol 5 ◽

pp. 121-126 ◽

Cited By ~ 7

Author(s):

Tobias Weber ◽

Robert Georgii ◽

Peter Böni

Keyword(s):

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Experiment Planning

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Integrated open-source software for multiscale electrophysiology

Scientific Data ◽

10.1038/s41597-019-0242-z ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 2

Author(s):

Konstantinos Nasiotis ◽

Martin Cousineau ◽

François Tadel ◽

Adrien Peyrache ◽

Richard M. Leahy ◽

...

Keyword(s):

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Analysis Data ◽

Open Science ◽

Dense Array ◽

Unrestricted Access ◽

Research Transparency ◽

Programming Skills ◽

User Friendly

Abstract The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

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