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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Screening a knowledge‐based library of low molecular weight compounds against the proline biosynthetic enzyme 1‐pyrroline‐5‐carboxylate 1 ( PYCR1)

Abstract Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H‐dependent reduction of Δ 1 ‐pyrroline‐5‐carboxylate toL‐proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of thePYCR1gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X‐ray crystallography and kinetic assays to determine affinity parameters. The library was counter‐screened against human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)‐tetrahydro‐2H‐pyran‐2‐carboxylic acid (70 μM) has higher affinity than the current best tool compoundN‐formyl‐l‐proline, is 30 times more specific for PYCR1 over human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure‐affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1‐hydroxyethane‐1‐sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed withl‐pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗
NASA NTRS2016

The Astrobiology Primer v2.0

Astrobiology is the science that seeks to understand the story of life in our universe. Astrobiology includes investigation of the conditions that are necessary for life to emerge and flourish, the origin of life, the ways that life has evolved and adapted to the wide range of environmental conditions here on Earth, the search for life beyond Earth, the habitability of extraterrestrial environments, and consideration of the future of life here on Earth and elsewhere. It therefore requires knowledge of physics, chemistry, biology, and many more specialized scientific areas including astronomy, geology, planetary science, microbiology, atmospheric science, and oceanography. However, astrobiology is more than just a collection of different disciplines. In seeking to understand the full story of life in the Universe in a holistic way, astrobiology asks questions that transcend all these individual scientific subjects. Astrobiological research potentially has much broader consequences than simply scientific discovery, as it includes questions that have been of great interest to human beings for millennia (e.g., are we alone?) and raises issues that could affect the way the human race views and conducts itself as a species (e.g., what are our ethical responsibilities to any life discovered beyond Earth?).

Domagal-Goldman, Shawn D.↗
NASA NTRS1993

MARIKA - A model revision system using qualitative analysis of simulations

This paper describes portions of a novel system called MARIKA (Model Analysis and Revision of Implicit Key Assumptions) to automatically revise a model of the normal human orientation system. The revision is based on analysis of discrepancies between experimental results and computer simulations. The discrepancies are calculated from qualitative analysis of quantitative simulations. The experimental and simulated time series are first discretized in time segments. Each segment is then approximated by linear combinations of simple shapes. The domain theory and knowledge are represented as a constraint network. Incompatibilities detected during constraint propagation within the network yield both parameter and structural model alterations. Interestingly, MARIKA diagnosed a data set from the Massachusetts Eye and Ear Infirmary Vestibular Laboratory as abnormal though the data was tagged as normal. Published results from other laboratories confirmed the finding. These encouraging results could lead to a useful clinical vestibular tool and to a scientific discovery system for space vestibular adaptation.

Groleau, Nicolas↗
NASA NTRS1990

Search techniques for near-earth asteroids

Knowledge of the near-earth asteroids (Apollo, Amor, and Aten groups) has increased enormously over the last 10 to 15 years. This has been due in large part to the success of programs that have systematically searched for these objects. These programs have been motivated by the apparent relationships of the near-earth asteroids to terrestrial impact cratering, meteorites, and comets, and their relative accessibility for asteroid missions. Discovery of new near-earth asteroids is fundamental to all other studies, from theoretical modeling of their populations to the determination of their physical characteristics by various remote-sensing techniques. The methods that have been used to find these objects are reviewed, and ways in which the search for near-earth asteroids can be expanded are discussed.

Helin, E. F.↗
NASA NTRSDate not supplied

Improving GES Disc Data Search and Discovery Through AI Metadata Augmentation

NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.

Kendall Gilbert↗
NASA NTRS2002

Mars Infrared Spectroscopy: From Theory and the Laboratory To Field Observations

The continuity and timely implementation of the Mars exploration strategy relies heavily on the ability of the planetary community to interpret infrared spectral data. However, the increasing mission rate, data volume, and data variety, combined with the small number of spectroscopists within the planetary community, will require a coordinated community effort for effective and timely interpretation of the newly acquired and planned data sets. Relevant spectroscopic instruments include the 1996 TES, 2001 THEMIS, 2003 Pancam, 2003 Mini-TES, 2003 Mars Express OMEGA, 2003 Mars Express PFS, and 2005 CFUSM. In light of that, leaders of the Mars spectral community met June 4-6 to address the question: What terrestrial theoretical, laboratory, and field studies are most needed to best support timely interpretations of current and planned visible infrared spectrometer data sets, in light of the Mars Program goals? A primary goal of the spectral community is to provide a reservoir of information to enhance and expand the exploration of Mars. Spectroscopy has a long history of providing the fundamental compositional discoveries in the solar system, from atmospheric constituents to surface mineralogy, from earth-based to spacecraft-based observations. However, such spectroscopic compositional discoveries, especially surface mineralogies, have usually come after long periods of detailed integration of remote observations, laboratory analyses, and field measurements. Spectroscopic information of surfaces is particularly complex and often is confounded by interference of broad, overlapping absorption features as well as confusing issues of mixtures, coatings, and grain size effects. Thus some spectroscopic compositional discoveries have come only after many years of research. However, we are entering an era of Mars exploration with missions carrying sophisticated spectrometers launching about every 2 years. It is critical that each mission provide answers to relevant questions to optimize the success of the next mission. That will not occur effectively unless the spectroscopic remote sensing data can be processed and understood on an approximate 2-year rate. Our current knowledge of spectral properties of materials and confounding effects of the natural environment are note well enough understood for the accurate interpretations needed for such ambitious and time critical exploration objectives. This workshop focused on identify ing critical gaps in moving the field towards the goal of rapid and accurate analysis and interpretation.

Kirkland, Laurel↗
NASA NTRSDate not supplied

The Radiation Biology Ontology: A New Tool Supporting FAIR Principles Across Radiation Biology Facilitating Data Discovery and Integration

Development of the Radiation Biology Ontology (RBO) was motivated by the need for a comprehensive, well-structured ontology for encoding radiation biology metadata. The primary use-cases were archiving data in the STORE database (https://www.storedb.org/), the repository for the RadoNorm Project, and in GeneLab (https://genelab.nasa.gov), NASA’s ‘omics database. The scope of radiobiology research ranges from physics to radiation oncology to socio-legal studies; no existing ontology has the necessary breadth or depth. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR radiation biology data.

ontology↗
NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗
NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗
NASA NTRS1994

Cometary Coma Chemical Composition (C4) Mission

Cometary exploration remains of great importance to virtually all of space science. Because comets are presumed to be remnants of the early solar nebula, they are expected to provide fundamental knowledge as to the origin and development of the solar system as well as to be key to understanding of the source of volatiles and even life itself in the inner solar system. Clearly the time for a detailed study of the composition of these apparent messages from the past has come. A comet rendezvous mission, the Cometary Coma Chemical Composition (C4) Mission, is now being studied as a candidate for the new Discovery program. This mission is a highly-focussed and usefully-limited subset of the Cometary Rendezvous Asteroid Flyby (CRAF) Mission. The C4 mission will concentrate on measurements that will produce an understanding of the composition and physical makeup of a cometary nucleus. The core science goals of the C4 mission are 1) to determine the chemical, elemental, and isotopic composition of a cometary nucleus and 2) to characterize the chemical and isotopic nature of its atmosphere. A related goal is to obtain temporal information about the development of the cometary coma as a function of time and orbital position. The four short-period comets -- Tempel 1, Tempel 2, Churyumov-Gerasimenko, and Wirtanen -which all appear to have acceptable dust production rates, were identified as candidate targets. Mission opportunities have been identified beginning as early as 1998. Tempel I with a launch in 1999, however, remains the baseline comet for studies of and planning the C4 mission. The C4 mission incorporates two science instruments and two engineering instruments in the payload to obtain the desired measurements. The science instruments include an advanced version of the Cometary Ice and Dust Experiment (CIDEX), a mini-CIDEX with a sample collection system, an X-ray Fluorescence Spectrometer and a Pyrolysis-Gas Chromatograph, and a simplified version of the Neutral Gas and Ion Mass Spectrometer (NIGMS). Both of these instruments have substantial heritage as they are based on those developed for the CRAF Mission. The engineering instruments include a simplified Comet Dust Environmental Monitor (SCODEM) and a navigational Camera, NAVCAM. While neither of the instruments will be permitted to establish science requirements, it is anticipated that significant science return will be accomplished Radio science will also be included.

Carle, Glenn C.↗
NASA NTRS2010

Testing Cosmic Inflation

The Cosmic Microwave Background (CMB) has provided a wealth of information about the history and physics of the early Universe. Much progress has been made on uncovering the emerging Standard Model of Cosmology by such experiments as COBE and WMAP, and ESA's Planck Surveyor will likely increase our knowledge even more. Despite the success of this model, mysteries remain. Currently understood physics does not offer a compelling explanation for the homogeneity, flatness, and the origin of structure in the Universe. Cosmic Inflation, a brief epoch of exponential expansion, has been posted to explain these observations. If inflation is a reality, it is expected to produce a background spectrum of gravitational waves that will leave a small polarized imprint on the CMB. Discovery of this signal would give the first direct evidence for inflation and provide a window into physics at scales beyond those accessible to terrestrial particle accelerators. I will briefly review aspects of the Standard Model of Cosmology and discuss our current efforts to design and deploy experiments to measure the polarization of the CMB with the precision required to test inflation.

Chuss, David↗
NASA NTRS2005

Cutting Silica Aerogel for Particle Extraction

The detailed laboratory analyses of extraterrestrial particles have revolutionized our knowledge of planetary bodies in the last three decades. This knowledge of chemical composition, morphology, mineralogy, and isotopics of particles cannot be provided by remote sensing. In order to acquire these detail information in the laboratories, the samples need be intact, unmelted. Such intact capture of hypervelocity particles has been developed in 1996. Subsequently silica aerogel was introduced as the preferred medium for intact capturing of hypervelocity particles and later showed it to be particularly suitable for the space environment. STARDUST, the 4th NASA Discovery mission to capture samples from 81P/Wild 2 and contemporary interstellar dust, is the culmination of these new technologies. In early laboratory experiments of launching hypervelocity projectiles into aerogel, there was the need to cut aerogel to isolate or extract captured particles/tracks. This is especially challenging for space captures, since there will be many particles/tracks of wide ranging scales closely located, even collocated. It is critical to isolate and extract one particle without compromising its neighbors since the full significance of a particle is not known until it is extracted and analyzed. To date, three basic techniques have been explored: mechanical cutting, lasers cutting and ion beam milling. We report the current findings.

Tsou, P.↗
NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗
NASA NTRS2016

The Sustainability of Habitability on Terrestrial Planets: Insights, Questions, and Needed Measurements from Mars for Understanding the Evolution of Earth-Like Worlds

What allows a planet to be both within a potentially habitable zone and sustain habitability over long geologic time? With the advent of exoplanetary astronomy and the ongoing discovery of terrestrial-type planets around other stars, our own solar system becomes a key testing ground for ideas about what factors control planetary evolution. Mars provides the solar systems longest record of the interplay of the physical and chemical processes relevant to habitability on an accessible rocky planet with an atmosphere and hydrosphere. Here we review current understanding and update the timeline of key processes in early Mars history. We then draw on knowledge of exoplanets and the other solar system terrestrial planets to identify six broad questions of high importance to the development and sustaining of habitability (unprioritized): (1) Is small planetary size fatal? (2) How do magnetic fields influence atmospheric evolution? (3) To what extent does starting composition dictate subsequent evolution, including redox processes and the availability of water and organics? (4) Does early impact bombardment have a net deleterious or beneficial influence? (5) How do planetary climates respond to stellar evolution, e.g., sustaining early liquid water in spite of a faint young Sun? (6) How important are the timescales of climate forcing and their dynamical drivers? Finally, we suggest crucial types of Mars measurements (unprioritized) to address these questions: (1) in situ petrology at multiple units/sites; (2) continued quantification of volatile reservoirs and new isotopic measurements of H, C, N, O, S, Cl, and noble gases in rocks that sample multiple stratigraphic sections; (3) radiometric age dating of units in stratigraphic sections and from key volcanic and impact units; (4) higher-resolution measurements of heat flux, subsurface structure, and magnetic field anomalies coupled with absolute age dating. Understanding the evolution of early Mars will feed forward to understanding the factors driving the divergent evolutionary paths of the Earth, Venus, and thousands of small rocky extra solar planets yet to be discovered.

rocky exoplanets↗
DOE OSTI2025

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗
DOE OSTI2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗