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At least 1,747 records · Page 97

Syntgen: a system to generate temporal networks with user-specified topology

Abstract In the last few years, the study of temporal networks has progressed markedly. The evolution of clusters of nodes (or communities) is one of the major focus of these studies. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here, we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for graphic sequences of inter- and intracluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distance between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis.

Pereira, Luis Ramada↗

Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and P l a n c k thermal Sunyaev-Zel’dovich effect observations. II. Modeling and constraints on halo pressure profiles

Hot, ionized gas leaves an imprint on the cosmic microwave background via the thermal Sunyaev-Zel’dovich (tSZ) effect. The cross-correlation of gravitational lensing (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) is a powerful probe of the thermal state of ionized baryons throughout the Universe and is sensitive to effects such as baryonic feedback. In a companion paper (Gatti et al. Phys. Rev. D 105, 123525 (2022)), we present tomographic measurements and validation tests of the cross-correlation between Galaxy shear measurements from the first three years of observations of the Dark Energy Survey and tSZ measurements from a combination of Atacama Cosmology Telescope and Planck observations. In this work, we use the same measurements to constrain models for the pressure profiles of halos across a wide range of halo mass and redshift. We find evidence for reduced pressure in low-mass halos, consistent with predictions for the effects of feedback from active Galactic nuclei. We infer the hydrostatic mass bias (B ≡ M 500c /M SZ from our measurements, finding B = 1.8 ± 0.1 when adopting the Planck-preferred cosmological parameters. We additionally find that our measurements are consistent with a nonzero redshift evolution of B, with the correct sign and sufficient magnitude to explain the mass bias necessary to reconcile cluster count measurements with the Planck-preferred cosmology. Our analysis introduces a model for the impact of intrinsic alignments (IAs) of galaxy shapes on the shear-tSZ correlation. We show that IA can have a significant impact on these correlations at current noise levels.

79 ASTRONOMY AND ASTROPHYSICS↗

Using factor analysis to identify neuromuscular synergies during treadmill walking

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

NASA Center JSC↗

Parametric Testing of Launch Vehicle FDDR Models

For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.

Schumann, Johann↗

A TALE OF A RICH CLUSTER AT z ∼ 0.8 AS SEEN BY THE STAR FORMATION HISTORIES OF ITS EARLY-TYPE GALAXIES

We present a detailed stellar population analysis for a sample of 24 early-type galaxies (ETGs) belonging to the rich cluster RX J0152.7-1357 at z = 0.83. We have derived the age, metallicity, abundance pattern, and star formation history (SFH) for each galaxy individually to further characterize this intermediate-z reference cluster. We then study how these stellar population parameters depend on the local environment. This provides a better understanding on the formation timescales and subsequent evolution of the substructures in this cluster. We have also explored the evolutionary link between z ∼ 0.8 ETGs and those in the local universe by comparing the trends that the stellar population parameters followed with galaxy velocity dispersion at each epoch. We find that the ETGs in Coma are consistent with being the (passively evolving) descendants of the ETG population in RX J10152.7-1357. Furthermore, our results favor a downsizing picture, where the subclumps centers were formed first. These central parts contain the most massive galaxies, which formed the bulk of their stars in a short, burst-like event at high z. On the contrary, the cluster outskirts are populated with less-massive, smaller galaxies that show a wider variety of SFHs. In general, they present extended star formation episodes over cosmic time, which seems to be related to their posterior incorporation into the cluster around 4 Gyr after the initial event of formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli , which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-means clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis , Pseudomonas aeruginosa , Thermus thermophilus , and Staphylococcus aureus . We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli . As a result, this analysis produces insights into improving the design of gene expression experiments.

59 BASIC BIOLOGICAL SCIENCES↗

Critical Role of the Interfacial Layer in Associating Polymers with Microphase Separation

Polymers with dynamic (transient) bonds, often called associating polymers, have been attracting significant attention in recent years due to their unique viscoelastic properties, self-healing ability, and recyclability. Nevertheless, understanding the mechanisms and the factors controlling their macroscopic properties remains limited due to the higher complexity introduced by the dynamic bonds. Here in this study, small-angle X-ray scattering (SAXS), broadband dielectric spectroscopy (BDS), and rheology were applied to unravel the structure and dynamics of telechelic associating polymers with different molecular weights. SAXS measurements revealed phase separation of the functional end groups with an average cluster size of ~2–3 nm and the distance between clusters controlled by the chain length. Borrowing the interfacial layer model analysis of BDS data from the polymer nanocomposite field, we demonstrated the presence of an interfacial polymer layer with a thickness of ~0.7–0.9 nm surrounding these clusters. Rheological measurements showed quantitatively that the presence of the interfacial layer significantly alters the viscoelastic behavior of these materials, indicating the crucial role of the interfacial layer in defining the macroscopic mechanical properties of the studied telechelic materials. The presented results emphasize that phase separation of the functional groups in associating polymers leads to very significant changes of the viscoelastic properties, opening a promising avenue in the design of novel functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated cosmological probes: concordance quantified

Assessing the consistency of parameter constraints derived from different cosmological probes is an important way to test the validity of the underlying cosmological model. In an earlier work [1], we computed constraints on cosmological parameters for ΛCDM from an integrated analysis of CMB temperature anisotropies and CMB lensing from Planck, galaxy clustering and weak lensing from SDSS, weak lensing from DES SV as well as Type Ia supernovae and Hubble parameter measurements. In this work, we extend this analysis and quantify the concordance between the derived constraints and those derived by the Planck Collaboration as well as WMAP9, SPT and ACT. As a measure for consistency, we use the Surprise statistic [2], which is based on the relative entropy. In the framework of a flat ΛCDM cosmological model, we find all data sets to be consistent with one another at a level of less than 1σ. We highlight that the relative entropy is sensitive to inconsistencies in the models that are used in different parts of the analysis. In particular, inconsistent assumptions for the neutrino mass break its invariance on the parameter choice. When consistent model assumptions are used, the data sets considered in this work all agree with each other and ΛCDM, without evidence for tensions.

79 ASTRONOMY AND ASTROPHYSICS↗

Detection of Lyman-alpha emission from a triply imaged z = 6.85 galaxy behind MACS J2129.4-0741

We report the detection of Lyα emission at ∼9538 Å in the Keck/DEIMOS and Hubble Space Telescope WFC3 G102 grism data from a triply imaged galaxy at z=6.846±0.001 behind galaxy cluster MACS J2129.4−0741. Combining the emission line wavelength with broadband photometry, line ratio upper limits, and lens modeling, we rule out the scenario that this emission line is [O ii] at z = 1.57. After accounting for magnification, we calculate the weighted average of the intrinsic Lyα luminosity to be ∼1.3×10{sup 42} erg s{sup −1} and Lyα equivalent width to be 74 ± 15 Å. Its intrinsic UV absolute magnitude at 1600 Å is −18.6 ± 0.2 mag and stellar mass (1.5±0.3)×10{sup 7} M{sub ⊙}, making it one of the faintest (intrinsic L{sub UV}∼0.14 L{sub UV}{sup ∗}) galaxies with Lyα detection at z∼7 to date. Its stellar mass is in the typical range for the galaxies thought to dominate the reionization photon budget at z≳7; the inferred Lyα escape fraction is high (≳10%), which could be common for sub-L* z≳7 galaxies with Lyα emission. This galaxy offers a glimpse of the galaxy population that is thought to drive reionization, and it shows that gravitational lensing is an important avenue for probing the sub-L* galaxy population.

79 ASTRONOMY AND ASTROPHYSICS↗

Dilute Pd/Au Alloy Nanoparticles Embedded in Colloid-Templated Porous SiO 2 : Stable Au-Based Oxidation Catalysts

Dilute alloy materials hold great promise for enhancing selectivity in catalytic reactions. A major challenge with such catalytic materials is developing supported alloy nanoparticles (NPs) with a catalytically optimal composition that are stable with respect to sintering. Here, we demonstrate that NP Pd/Au catalysts with minor concentrations of Pd prepared by a colloid-templating approach are active for oxygen dissociation and catalytic oxidation, as exemplified by CO oxidation. Using electron microscopic imaging, infrared spectroscopy, and X-ray photoelectron spectroscopy, we demonstrate that Pd is stabilized within the Au nanoparticle in its metallic state with minor amounts of Pd at the surface. The Pd–Au nanoparticles are embedded in the colloidally templated silica and form a thermally stable catalyst at high temperature. Surface analysis by diffuse reflectance infrared spectroscopy indicates that the Pd atomic distribution at the surface varies with the bulk concentration, forming isolated Pd atoms at 2% Pd and a mixture of Pd monomers and small Pd clusters at 9% Pd. X-ray absorption fine structure analysis indicates that Pd is well distributed in the bulk of the nanoparticle. In conclusion, in-depth understanding of this new class of catalytic materials opens the way to a wide array of possibilities for crucial enhancement of activity and selectivity in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

4.46 Ga Zircons Anchor Chronology of Lunar Magma Ocean

The crystallisation ages of lunar samples provide critical constraints on the minimum formation age of the Moon and its early evolution. Zircon crystals from Apollo 17 lunar impact melt breccia 72255 preserve ancient domains with a concordant average uranium-lead radiometric date of 4460 ± 31 Ma (Zhang et al., 2021), the oldest lunar zircon yet reported. To assess the possible mobility of radiogenic lead in zircon, which may lead to redistribution and clustering of Pb atoms that may cause a U-Pb age bias (Valley et al., 2014), we investigated a zircon grain from Zhang et al. (2021) by atom probe tomography (APT). The atomic spatial resolution analysis of individual mineral grains demonstrates the absence of nanoscale clustering of lead, which supports a 4.46 Ga ancient formation age for lunar zircon in sample 72255. This age pushes back the age of the first preserved lunar crust by ∼40 Myr and provides a minimum formation age for the Moon within 110 Myr after the formation of the solar system.

atom probe tomography↗

Extended main sequence turnoffs in intermediate-age star clusters: a correlation between turnoff width and early escape velocity

We present a color-magnitude diagram analysis of deep Hubble Space Telescope imaging of a mass-limited sample of 18 intermediate-age (1-2 Gyr old) star clusters in the Magellanic Clouds, including eight clusters for which new data were obtained. We find that all star clusters in our sample feature extended main-sequence turnoff (eMSTO) regions that are wider than can be accounted for by a simple stellar population (including unresolved binary stars). FWHM widths of the MSTOs indicate age spreads of 200-550 Myr. We evaluate the dynamical evolution of clusters with and without initial mass segregation. Our main results are (1) the fraction of red clump (RC) stars in secondary RCs in eMSTO clusters scales with the fraction of MSTO stars having pseudo-ages of ≲1.35 Gyr; (2) the width of the pseudo-age distributions of eMSTO clusters is correlated with their central escape velocity v {sub esc}, both currently and at an age of 10 Myr. We find that these two results are unlikely to be reproduced by the effects of interactive binary stars or a range of stellar rotation velocities. We therefore argue that the eMSTO phenomenon is mainly caused by extended star formation within the clusters; and (3) we find that v {sub esc} ≥ 15 km s{sup –1} out to ages of at least 100 Myr for all clusters featuring eMSTOs, and v {sub esc} ≤ 12 km s{sup –1} at all ages for two lower-mass clusters in the same age range that do not show eMSTOs. We argue that eMSTOs only occur for clusters whose early escape velocities are higher than the wind velocities of stars that provide material from which second-generation stars can form. The threshold of 12-15 km s{sup –1} is consistent with wind velocities of intermediate-mass asymptotic giant branch stars and massive binary stars in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster–solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi 38 O 45 ] core. Upon dissolution of crystalline [Bi 6 O 5 (OH) 3 (NO 3 ) 5 ]∙3 H 2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi 38 O 45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bi x O y ] structures based on the [Bi 38 O 45 ] framework are tested against the data. [Bi 22 O 26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A High-resolution Multiband Survey of Westerlund 2 with the Hubble Space Telescope. III. The Present-day Stellar Mass Function

We present a detailed analysis of the spatial distribution of the stellar population and the present-day mass function (PDMF) of the Westerlund 2 (Wd2) region using the data from our high-resolution multiband survey with the Hubble Space Telescope. We used state-of-the-art artificial star tests to determine spatially resolved completeness maps for each of the broadband filters. We reach a level of completeness of 50% down to F555W=24.8 mag (0.7 M{sub ⊙}) and F814W=23.3 mag (0.2 M{sub ⊙}) in the optical and F125W=20.2 mag and F160W=19.4 mag (both 0.12 M{sub ⊙}) in the infrared throughout the field of view. We had previously reported that the core of Wd2 consists of two clumps: namely the main cluster and the northern clump. From the spatial distribution of the completeness-corrected population, we find that their stellar surface densities are 1114 stars pc{sup −2} and 555 stars pc{sup −2}, respectively, down to F814W=21.8 mag. We find that the PDMF of Wd2 has a slope of Γ=−1.46±0.06, which translates to a total stellar cluster mass of (3.6±0.3)⋅10{sup 4} M{sub ⊙}. The spatial analysis of the PDMF reveals that the cluster population is mass-segregated and most likely primordial. In addition, we report the detection of a stellar population of spatially uniformly distributed low-mass (<0.15 M{sub ⊙}) stars, extending into the gas ridges of the surrounding gas and dust cloud, as well as a confined region of reddened stars, likely caused by a foreground CO cloud. We find hints that a cloud–cloud collision might be the origin of the formation of Wd2.

79 ASTRONOMY AND ASTROPHYSICS↗

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Lee, J.↗

Mitigate: An Adaptive Network Data Anonymization Tool Using Condensation-Based Differential Privacy

Modern network devices collect a large amount of data that can be analyzed to identify bottlenecks, anomalies, cyber-attacks, etc. Therefore, there is often a need to analyze such collections of network data quite often by an external expert or by the research community. However, these collections of data contain sensitive, proprietary information. In order for the network data to be shared, it must first be anonymized. The overall objective of this project is to develop an innovative privacy management tool to anonymize network data and achieve sufficient privacy, acceptable data utility, and efficient data analysis at the same time. No existing anonymization methods can achieve all of these at the same time. The core of this technology is a differential private clustering algorithm that provides strong privacy protection, preserves data properties important for subsequent analysis, and allows the party receiving the anonymized data to conduct analysis directly on anonymized data without the need of decryption or any extra processing. The research carried out was to design, implement and verify a solution to this problem by completing the following tasks: 1) developing the core technology; 2) developing a context based method that automatically recommends fields that must be anonymized; 3) conducted experiments showing superior results using our approach compared to existing tools, and 4) developed an intuitive but basic user interface. The research that was conducted generated novel algorithmic techniques that utilize state-of-the-art methods such as condensation, differential privacy preservation, clustering, automated tuning based on contextual awareness, and recommendation techniques to specify columns to users for anonymization leading to optimal privacy that allows research analysis on the dataset. Experiments were conducted to evaluate the efficacy of these novel algorithmic techniques by performing analysis on original non-anonymized datasets, then conducting analysis on the same yet anonymized datasets and comparing the results of the analyses. Overall, the anonymized analysis results were within 1% of the original results, verifying that the generated technology not only guarantees a high level of privacy but also enables research analysis as if it were conducted on the original dataset. Potential applications of this technology include anonymization of any type of structured network datasets that contain sensitive identifiers, such as IP addresses, that can be used in multiple applications. For example, to create an AI or machine learning model for cyber security, e.g., to detect attacks, or for performance analysis, e.g., identify bottlenecks or predict performance. In addition, a market analysis that was conducted for potential applications of this technology identified a broader range of applications of our anonymization technology beyond the network sector that includes healthcare, banking, insurance, securities, finance (FISB), data brokering, cloud services, ad sales, and government.

97 MATHEMATICS AND COMPUTING↗

SIMULATING ASTRO-H OBSERVATIONS OF SLOSHING GAS MOTIONS IN THE CORES OF GALAXY CLUSTERS

Astro-H will be the first X-ray observatory to employ a high-resolution microcalorimeter, capable of measuring the shift and width of individual spectral lines to the precision necessary for estimating the velocity of the diffuse plasma in galaxy clusters. This new capability is expected to bring significant progress in understanding the dynamics, and therefore the physics, of the intracluster medium. However, because this plasma is optically thin, projection effects will be an important complicating factor in interpreting future Astro-H measurements. To study these effects in detail, we performed an analysis of the velocity field from simulations of a galaxy cluster experiencing gas sloshing and generated synthetic X-ray spectra, convolved with model Astro-H Soft X-ray Spectrometer (SXS) responses. We find that the sloshing motions produce velocity signatures that will be observable by Astro-H in nearby clusters: the shifting of the line centroid produced by the fast-moving cold gas underneath the front surface, and line broadening produced by the smooth variation of this motion along the line of sight. The line shapes arising from inviscid or strongly viscous simulations are very similar, indicating that placing constraints on the gas viscosity from these measurements will be difficult. Our spectroscopic analysis demonstrates that, for adequate exposures, Astro-H will be able to recover the first two moments of the velocity distribution of these motions accurately, and in some cases multiple velocity components may be discerned. The simulations also confirm the importance of accurate treatment of point-spread function scattering in the interpretation of Astro-H/SXS spectra of cluster plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗

MultiAlign: a multiple LC-MS analysis tool for targeted omics analysis

MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and LC elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. Clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs.

Environmental Molecular Sciences Laboratory↗