Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data clustering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The radius of the quiescent neutron star in the globular cluster M13

X-ray spectra of quiescent low-mass X-ray binaries containing neutron stars can be fit with atmosphere models to constrain the mass and the radius. Mass-radius constraints can be used to place limits on the equation of state of dense matter. In this paper, we perform fits to the X-ray spectrum of a quiescent neutron star in the globular cluster M13, utilizing data from ROSAT, Chandra, and XMM–Newton, and constrain the mass–radius relation. Assuming an atmosphere composed of hydrogen and a 1.4 M ⊙ neutron star, we find the radius to be R NS = 12.2 +1.5 -1.1 km, a significant improvement in precision over previous measurements. Incorporating an uncertainty on the distance to M13 relaxes the radius constraints slightly and we find R NS = 12.3 +1.9 -1.7 km (for a 1.4M ⊙ neutron star with a hydrogen atmosphere), which is still an improvement in precision over previous measurements, some of which do not consider distance uncertainty. Finally, we also discuss how the composition of the atmosphere affects the derived radius, finding that a helium atmosphere implies a significantly larger radius.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Low Altitude AVIRIS Data for Mapping Land Cover in Yellowstone National Park: Use of Isodata Clustering Techniques

Yellowstone National Park (YNP) contains a diversity of land cover. YNP managers need site-specific land cover maps, which may be produced more effectively using high-resolution hyperspectral imagery. ISODATA clustering techniques have aided operational multispectral image classification and may benefit certain hyperspectral data applications if optimally applied. In response, a study was performed for an area in northeast YNP using 11 select bands of low-altitude AVIRIS data calibrated to ground reflectance. These data were subjected to ISODATA clustering and Maximum Likelihood Classification techniques to produce a moderately detailed land cover map. The latter has good apparent overall agreement with field surveys and aerial photo interpretation.

Spruce, Joe↗
DOE OSTI2021

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Structure of Ne 20 states in resonance O 16 + α elastic scattering

Background: The nuclear structure of the cluster bands in 20 Ne presents a challenge for different theoretical approaches. It is especially difficult to explain the broad 0 + , 2 + states at 9 MeV excitation energy. Simultaneously, it is important to obtain more reliable experimental data for these levels in order to quantitatively assess the theoretical framework. Purpose: To obtain new data on 20 Ne α- cluster structure. Method: Thick target inverse kinematics technique was used to study the 16 O+α resonance elastic scattering and the data were analyzed using an R matrix approach. The 20 Ne spectrum, the cluster and nucleon spectroscopic factors were calculated using cluster-nucleon configuration interaction model (CNCIM). Results: We determined the parameters of the broad resonances in 20 Ne: 0 + level at 8.77 ± 0.150 MeV with a width of 750 $^{+500}_{-220}$ keV; 2 + level at 8.75 ± 0.100 MeV with the width of 695 ± 120 keV; the width of 9.48 MeV level of 65 ± 20 keV and showed that 9.19 MeV, 2 + level (if exists) should have width ≤ 10 keV. The detailed comparison of the theoretical CNCIM predictions with the experimental data on cluster states was made. Conclusions: Our experimental results by the TTIK method generally confirm the adopted data on α-cluster levels in 20 Ne. The CNCIM gives a good description of the 20 Ne positive parity states up to an excitation energy of ~7 MeV, predicting reasonably well the excitation energy of the states and their cluster and single particle properties. At higher excitations, the qualitative disagreement with the experimentally observed structure is evident, especially for broad resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Experimental particle formation rates spanning tropospheric sulfuric acid and ammonia abundances, ion production rates, and temperatures

Abstract Binary nucleation of sulfuric acid and water as well as ternary nucleation involving ammonia are thought to be the dominant processes responsible for new particle formation (NPF) in the cold temperatures of the middle and upper troposphere. Ions are also thought to be important for particle nucleation in these regions. However, global models presently lack experimentally measured NPF rates under controlled laboratory conditions and so at present must rely on theoretical or empirical parameterizations. Here with data obtained in the European Organization for Nuclear Research CLOUD (Cosmics Leaving OUtdoor Droplets) chamber, we present the first experimental survey of NPF rates spanning free tropospheric conditions. The conditions during nucleation cover a temperature range from 208 to 298 K, sulfuric acid concentrations between 5 × 10 5 and 1 × 10 9 cm −3 , and ammonia mixing ratios from zero added ammonia, i.e., nominally pure binary, to a maximum of ~1400 parts per trillion by volume (pptv). We performed nucleation studies under pure neutral conditions with zero ions being present in the chamber and at ionization rates of up to 75 ion pairs cm −3 s −1 to study neutral and ion‐induced nucleation. We found that the contribution from ion‐induced nucleation is small at temperatures between 208 and 248 K when ammonia is present at several pptv or higher. However, the presence of charges significantly enhances the nucleation rates, especially at 248 K with zero added ammonia, and for higher temperatures independent of NH 3 levels. We compare these experimental data with calculated cluster formation rates from the Atmospheric Cluster Dynamics Code with cluster evaporation rates obtained from quantum chemistry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Molecular subtyping reveals immune alterations in IDH wild‐type lower‐grade diffuse glioma

Abstract Isocitrate dehydrogenase ( IDH ) wild‐type diffuse lower‐grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression‐based molecular classification of IDH wild‐type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild‐type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy‐three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild‐type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up‐regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A / CDKN2B , DMRTA1 , C9orf53 , and MTAP . Furthermore, we developed and validated a five‐gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild‐type diffuse LGGs and deepen our molecular understandi‐g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Wu, Fan↗
DOE OSTI2018

Mapping ecoregions under climate change: a case study from the biological ‘crossroads’ of three continents, Turkey

Context: Besides climate change vulnerability, most ecosystems are under threat from a history of improper land-use and conservation policies, yet there is little existing long-term ecological research infrastructure in Turkey. In regions with no ecological networks across large landscapes, ecoregion concept offers opportunities for characterizing the landscape under changing climate.Objectives: Aim is to develop contemporary and future quantitative ecoregions for Turkey based on climate model outputs, to identify climate change-sensitive areas of biodiversity and conservation significance, and to provide a framework for a comprehensive ecological observatory network design.Methods: Using Multivariate Spatio-Temporal Clustering and climate data contemporary and projected future distributions of Turkey’s ecoregions are delineated at several division levels.Results: Turkey’s contemporary ecoregions generally show a northward shift by the end of this century and the lengthening of the growing season across the country, especially eastward and northward. The increase in growing season length, along with the shift in precipitation seasonality and increasing growing season precipitation, shape future conditions within the climate change-sensitive areas. Apart from transboundary ecological and socioeconomic significance, these potentially vulnerable ecosystems also constitute the majority of Turkey’s biodiversity hotspots.Conclusions: Our study marks the first ‘ecoregionalization’ study for Turkey based on both contemporary and future climate scenarios. For countries like Turkey, where large-scale ecological networks have not been established, using such quantitative methodology for delineation of optimal ecoclimatic regions, and for mapping environments at risk from climate change provides an invaluable perspective for conservation planning strategies, and a framework for a comprehensive ecological observatory network design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A proteome-wide assessment of the oxidative stress paradigm for metal and metal-oxide nanomaterials in human macrophages

Responsible implementation of engineered nanomaterials (ENMs) into commercial applications is an important societal issue, driving demand for new approaches for rapid and comprehensive evaluation of their bioactivity and safety. An essential part of any research focused on identifying potential hazard of ENMs is the appropriate selection of biological endpoints to evaluate. Herein, we use a tiered strategy employing both targeted biological assays and untargeted quantitative proteomics to elucidate the biological responses of human macrophages across a library of metal/metal oxide ENMs, raised as priority ENMs for investigation by NIEHS’s Nanomaterial Health Implications Research (NHIR) program. Our results show that quantitative cellular proteome profiles readily distinguish ENM types based on their cytotoxic potential according to induction of biological processes and pathways involved in the cellular antioxidant response, TCA cycle, oxidative stress, endoplasmic reticulum stress, and immune responses as major processes impacted. Interestingly, pathway analysis of differentially abundant proteins also revealed new cell processes that were influenced by all ENMs independent of cytotoxic potential. These included pathways previously implicated as cellular adaptive mechanisms to low levels of oxidative stress, including cell adhesion, protein translation and protein targeting pathways. Unsupervised clustering of all data revealed the most striking proteome changes that differentiated ENM classes involved a small subset of proteins involved in the oxidative stess response (HMOX1), protein chaperone functions (HS71B, DNJB1), and autophagy (SQSTM), providing a potential new panel of markers of ENM-induced cell stress. To our knowledge, the results represent the most comprehensive profiling of the biological responses to a library of ENMs conducted using quantitative mass spectrometry-based proteomics. The results provide a basis to identify the patterns of a diverse set of cellular pathways and cell processes impacted by ENM exposure in an important immune cell type, laying the foundation for multivariate, pathway-level structure activity assessments of ENMs in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DMRG on Top of Plane-Wave Kohn–Sham Orbitals: A Case Study of Defected Boron Nitride

In this paper, we analyze the numerical aspects of the inherent multi reference density matrix renormalization group (DMRG) calculations on top of the periodic Kohn-Sham density functional theory using the complete active space approach. The potential of the framework is illustrated by studying hexagonal boron nitride nanoflakes embedding a charged single boron vacancy point defect by revealing a vertical energy spectrum with a prominent multireference character. We investigate the consistency of the DMRG energy spectrum from the perspective of sample size, basis size, and active space selection protocol. Results obtained from standard quantum chemical atom-centered basis calculations and plane-wave based counterparts show excellent agreement. Furthermore, we also discuss the spectrum of the periodic sheet which is in good agreement with extrapolated data of finite clusters. These results pave the way toward applying the DMRG method in extended correlated solid-state systems, such as point defect qubit in wide band gap semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibility

Mechanistic understanding of large molecule conversion and the discovery of suitable heterogeneous catalysts have been lagging due to the combinatorial inventory of intermediates and the inability of humans to enumerate all structures. Here, we introduce an automated framework to predict stable configurations on transition metal surfaces and demonstrate its validity for adsorbates with up to 6 carbon and oxygen atoms on 11 metals, enabling the exploration of ~10 8 potential configurations. It combines a graph enumeration platform, force field, multi-fidelity DFT calculations, and first-principles trained machine learning. Clusters in the data reveal groups of catalysts stabilizing different structures and expose selective catalysts for showcase transformations, such as the ethylene epoxidation on Ag and Cu and the lack of C-C scission chemistry on Au. Deviations from the commonly assumed atom valency rule of small adsorbates are also manifested. This library can be leveraged to identify catalysts for converting large molecules computationally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identification of the weak-to-strong transition in Alfvénic turbulence from space plasma

Abstract Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales in astrophysical and space plasma systems. Although the theory of anisotropic magnetohydrodynamic (MHD) turbulence has successfully described natural phenomena, its core prediction of an Alfvénic transition from weak to strong MHD turbulence when energy cascades from large to small scales has not been observationally confirmed. Here we report evidence for the Alfvénic weak-to-strong transition in small-amplitude, turbulent MHD fluctuations in Earth’s magnetosheath using data from four Cluster spacecraft. Our observations demonstrate the universal existence of strong turbulence accompanied by weak turbulent fluctuations on large scales. Moreover, we find that the nonlinear interactions of MHD turbulence are crucial to the energy cascade, as they broaden the cascade directions and fluctuating frequencies. The observed connection between weak and strong MHD turbulence systems may be present in many astrophysical environments, such as star formation, energetic particle transport, turbulent dynamos, and solar corona or solar wind heating.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Integrated analysis reveals that STAT3 is central to the crosstalk between HER/ErbB receptor signaling pathways in human mammary epithelial cells

Human epidermal growth factor receptors (HER, also known as ErbB) drive cellular proliferation, pro-survival and stress responses by activating several downstream kinases, in particular ERK, p38, JNK (SAPK), the PI3K/AKT, as well as various transcriptional regulators such as STAT3. When co-expressed, first three members of HER family (HER1-3) can form homo- and hetero-dimers. Based on the considerable evidence which suggest that every receptor dimer activates intracellular signaling pathways differentially, we hypothesized that the HER dimerization pattern is a better predictor of downstream signaling than the total receptor activation levels. We validated our hypothesis using a combination of model-based analysis to quantify the HER dimerization patterns and multi-factorial experiments where HER dimerization patterns and signaling crosstalk were rationally perturbed. We have measured the activation of HER1-3 receptors and of the sentinel signaling proteins ERK, AKT, p38, JNK, STAT3 as a function of time in a panel of human mammary epithelial (HME) cells expressing different levels of HER1-3 stimulated with various ligand combinations. Our analysis using multiple ways of clustering the activation data has confirmed that the HER receptor dimer is a better predictor of the signaling through p38, ERK and AKT pathways than the total HER receptor expression and activation levels. Targeted inhibition studies to identify the causal effects allowed us to obtain a consensus regulatory interaction model, which revealed that STAT3 occupies a central role in the crosstalk between the studied pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The importance of accounting for the Tolman correction to surface tension for nucleation and growth modeling of Fe clusters

Gibbs free energies of clusters are required for predictive modeling of cluster growth during condensation of a cooling vapor. Here, we present a straightforward method of calculating free energies of cluster formation using the data from molecular dynamics (MD) simulations. We apply this method to iron clusters having from 2 to 100 atoms. The energies obtained are verified by comparing to an MD-simulated equilibrium cluster size distribution in a sub-saturated vapor. We show that these free energies differ significantly from those obtained with a commonly used spherical cluster approximation, which relies on a surface tension coefficient of a flat surface, as it is used in the classical nucleation theory (CNT). We show that the spherical cluster approximation in CNT can be improved by using a cluster-size-dependent Tolman correction for the surface tension. The Tolman length and effective surface tension values were derived for iron clusters, and they significantly differ from the commonly used experimentally measured values. This improved approximation does not account for geometric magic number effects responsible for spikes and troughs in densities of neighbor cluster sizes. Nonetheless, it allows to more accurately model cluster formation from a cooling vapor. It better reproduces the condensation timeline, overall shape of the cluster size distribution, average cluster size, and the distribution width. In contrast, using a constant surface tension coefficient (as done in CNT) resulted in incorrect condensation dynamics and cluster size distributions. The analytical expression for cluster nucleation rate from CNT was updated to account for the size-dependence of cluster surface tension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The prolate dark matter halo of the Andromeda galaxy

We present new limits on the global shape of the dark matter halo in the Andromeda galaxy using and generalizing non-spherical mass models developed by Hayashi and Chiba and compare our results with theoretical predictions of cold dark matter (CDM) models. This is motivated by the fact that CDM models predict non-spherical virialized dark halos, which reflect the process of mass assembly in the galactic scale. Applying our models to the latest kinematic data of globular clusters and dwarf spheroidal galaxies in the Andromeda halo, we find that the most plausible cases for Andromeda yield a prolate shape for its dark halo, irrespective of assumed density profiles. We also find that this prolate dark halo in Andromeda is consistent with theoretical predictions in which the satellites are distributed anisotropically and preferentially located along major axes of their host halos. It is a reflection of the intimate connection between galactic dark matter halos and the cosmic web. Therefore, our result is profound in understanding internal dynamics of halo tracers in Andromeda, such as orbital evolutions of tidal stellar streams, which play important roles in extracting the abundance of CDM subhalos through their dynamical effects on stream structures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Evidence of the ion cyclotron resonance at proton kinetic scales in the solar wind

The k-filtering and wave polarization techniques are applied to Cluster magnetic field data at four intervals of fast free (not connected to Earth's foreshock) solar wind. In addition to the commonly observed population of magnetic field fluctuations propagating at quasi-perpendicular angles to the global mean field B{sub 0}, a population of fluctuations propagating at quasi-parallel angles are also observed when no local plasma instability can be identified. At low wavenumbers (kv{sub A}/Ω{sub p} ≤ 0.6) both components are present, and have powers of similar strength, while at higher wavenumbers (kv{sub A}Ω{sub p} > 0.6) only the perpendicular component can be identified. Here v{sub A} and Ω{sub p} are the Alfvén speed and the proton (angular) gyration frequency, k denotes the wavenumber. The dispersion curve obtained (and the ratio of the magnitudes of left and right hand polarized fluctuations) shows a sharp transition (and decrease) at (kv{sub A}/Ω{sub p}) ∼ 0.6, which corresponds to a spacecraft frequency f {sub sc} = 0.32 Hz. At higher wavenumbers the measurements agree with previous studies indicating the presence of kinetic Alfvén wave (KAW) turbulence or a mixture of KAW turbulence and convected structures. The parallel component displays a scaling of k{sub ∥}{sup −δ} where the spectral index δ ranges between about 5/3 and 2 although the number of data points does not warrant an accurate determination. The origins of the observed parallel component are unclear. The presence of a parallel component is consistent with ion cyclotron waves, and we interpret the sharp drop of this component at higher wavenumbers as evidence that the ion cyclotron resonance is occurring in the solar wind intervals studied.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

WE-FG-BRA-08: Potential Role of the Glycolytic Oscillator in Acute Hypoxia in Tumors

Purpose: Oscillatory dynamics in acute hypoxia have been observed, but poorly understood. They have mostly been attributed to vascular perturbations, but no link has yet been made to metabolic causes. We set out to determine the fundamental frequencies and test for coherence in tumor oxygen dynamics and spatial properties. Methods: Severe combined immunodeficient (SCID) mice were inoculated onto bilateral flanks with human derived head and neck carcinoma (UW-SCC22) cell line xenografts. Oxygen dynamics were monitored in the tumor every minute for an hour using three modalities: blood oxygen level dependent - magnetic resonance imaging (BOLD-MRI), hemoglobin oxygen saturation photoacoustic, and locally manufactured optical probes for spectral fitting. A statistical test was used to separate fluctuating from non-fluctuating voxels and pixels in BOLD-MRI and photoacoustic data respectively. The power spectrum density (PSD) and the autocorrelation functions were calculated for the time series of each voxel, pixel and region, of the BOLD-MRI, photoacoustic or fiber optic data respectively. Results: Using all three techniques, intermittent oxygen dynamics with both coherent and incoherent signatures was observed in the tumors. Upon averaging the PSDs of fluctuating voxels and pixels, it was found that these oscillations occurred with periods of minutes to tens of minutes from all three approaches. Observations from the BOLD-MRI and photoacoustic data showed that clusters of voxels oscillated in a synchronized manner. Conclusion: We were able to use three different modalities to show that fluctuation in tumor oxygen is both coherent and incoherent, with periods of minutes to tens of minutes. These periods are very similar to those from the well-established metabolic, non-linear biomechanical phenomenon called the glycolytic oscillator. This may provide an additional explanation to the cause of cyclic hypoxia. Such dynamics could have profound implications in hypofractionated radiotherapy regiments and could help guide treatment and make it more patient specific. The authors would like to thank the University of Wisconsin Carbone Cancer Center (UWCCC) for the funds to complete this project. This work is also supported in part by NIH/NCI P30 CA014520- UW Comprehensive Cancer Center Support”.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

HPC ODA Commons [SWR-26-003]

HPC ODA Commons is a community-driven platform for standardizing HPC operational data analytics. HPC sites generate enormous volumes of operational data - scheduler logs, accounting records, monitoring streams - but turning that data into actionable insight is needlessly hard. Each site builds bespoke parsers, schemas, and evaluation pipelines. Results can't be compared across institutions. Promising analytics ideas stay siloed because there's no shared language for describing the data, the experiments, or the outcomes. HPC ODA Commons fixes this by establishing community-governed contracts - versioned schemas, canonical artifacts, and benchmark recipes - that make ODA workflows discoverable, reproducible, and comparable. It pairs these standards with a practical, CLI-first toolkit that lets operators and researchers go from raw logs to standardized results without sending data off-cluster.

Menear, Kevin [National Laboratory of the Rockies ↗
DOE OSTI2018

A Model Integration Pipeline for the Improvement of Human Genome-Scale Metabolic Reconstructions

Abstract Metabolism has been a major field of study in the last years, mainly due to its importance in understanding cell physiology and certain disease phenotypes due to its deregulation. Genome-scale metabolic models (GSMMs) have been established as important tools to help achieve a better understanding of human metabolism. Towards this aim, advances in systems biology and bioinformatics have allowed the reconstruction of several human GSMMs, although some limitations and challenges remain, such as the lack of external identifiers for both metabolites and reactions. A pipeline was developed to integrate multiple GSMMs, starting by retrieving information from the main human GSMMs and evaluating the presence of external database identifiers and annotations for both metabolites and reactions. Information from metabolites was included into a graph database with omics data repositories, allowing clustering of metabolites through their similarity regarding database cross-referencing. Metabolite annotation of several older GSMMs was enriched, allowing the identification and integration of common entities. Using this information, as well as other metrics, we successfully integrated reactions from these models. These methods can be leveraged towards the creation of a unified consensus model of human metabolism.

Vieira, Vítor↗