Network Of Workstations Research Articles

Containerized Computing with DevOps Methodology Use on the Central Linux Cluster at NRC “Kurchatov Institute”—IHEP

Containerized Computing with DevOps Methodology Use on the Central Linux Cluster at NRC “Kurchatov Institute”—IHEP

The Distribution of Boars Spermatozoa in Morphometrically Distinct Subpopulations after In Vitro Exposure to Radiofrequency Electromagnetic Radiation at 2500 MHz and Their Motility.

Anthropogenic radiofrequency electromagnetic radiation (RF-EMR) from wireless technologies has increased dramatically. The boar semen used for artificial insemination is essential in sustaining the pig industry, and additionally it is also exposed to the effects of the RF-EMR of wireless technologies. Furthermore, there are no data on the effects of RF-EMR on semen quality, and this is the first analysis of sperm's morphometric parameters for assessing the effect of RF-EMR on the spermatozoa subpopulations of boars. This study investigated the effect of RF-EMR on in vitro exposed breeding boar semen spermatozoa motility and the proportions of spermatozoa subpopulations according to their morphometric head and tail parameters. The semen samples of 12 boars were divided into control and experimental groups. The samples in the experimental group were exposed in a gigahertz transverse electromagnetic chamber at a frequency of 2500 MHz (the frequency band used in 5G technology) and an electric field strength of 10 Vm-1 for two hours. After exposure, the spermatozoa motility was evaluated for both groups. A morphometric analysis of the semen smears was performed using SFORM software (Version 1.0; VAMS, Zagreb, Croatia). The progressive spermatozoa motility was significantly reduced in the experimental group (74.7% vs. 85.7%). PC analysis and cluster analysis revealed two spermatozoa subpopulations: S1, spermatozoa with a more regular head shape and a smaller midpiece outline, and S2, spermatozoa with a more elongated head shape and a larger midpiece outline. The experimental semen samples had a greater proportion of the S1 spermatozoa subpopulation (68.2% vs. 64.4%). The effect of RF-EMR at 2500 MHz on the in vitro exposed boar semen resulted in decreased progressive spermatozoa motility and a lower proportion of the spermatozoa subpopulation with a higher fertilizing potential.

OctoFAS: A Two-Level Fair Scheduler That Increases Fairness in Network-Based Key-Value Storage

We identified a fairness problem in a network-based key-value storage system using Intel Storage Performance Development Kit (SPDK) in a multitenant environment. In such an environment, each tenant’s I/O service rate is not fairly guaranteed compared to that of other tenants. To address the fairness problem, we propose OctoFAS, a two-level fair scheduler designed to improve overall throughput and fairness among tenants. The two-level scheduler of OctoFAS consists of (i) inter-core scheduling and (ii) intra-core scheduling. Through inter-core scheduling, OctoFAS addresses the load imbalance problem that is inherent in SPDK on the storage server by dynamically migrating I/O requests from overloaded cores to underloaded cores, thereby increasing overall throughput. Intra-core scheduling prioritizes handling requests from starving tenants over well-fed tenants within core-specific event queues to ensure fair I/O services among multiple tenants. OctoFAS is deployed on a Linux cluster with SPDK. Through extensive evaluations, we found that OctoFAS ensures that the total system throughput remains high and balanced, while enhancing fairness by approximately 10% compared to the baseline, when both scheduling levels operate in a hybrid fashion.

A multicompartment population PK model to predict tenofovir and emtricitabine mucosal tissue concentrations for HIV prevention.

A priori use of mathematical modeling and simulation to predict outcomes from incomplete adherence or reduced frequency dosing strategies may mitigate the risk of clinical trial failure with HIV pre-exposure prophylaxis regimens. We developed a semi-physiologic population pharmacokinetic model for two antiretrovirals and their active intracellular metabolites in three mucosal tissues using pharmacokinetic data from a phase I, dose-ranging study. Healthy female volunteers were given a single oral dose of tenofovir disoproxil fumarate (150, 300, or 600 mg) or emtricitabine (100, 200, or 400 mg). Simultaneous co-modeling of all data was performed on a Linux cluster. A 16 compartment, bolus input, linear kinetic model best described the data, containing 986 observations in 23 individuals across three matrices and four analytes. Combined with a defined efficacious concentration target in mucosal tissues, this model can be used to optimize the dose and dosing frequency through Monte-Carlo simulations.

A comparative study of scalable multilevel preconditioners for cardiac mechanics

In this work, we provide a performance comparison between the Balancing Domain Decomposition by Constraints (BDDC) and the Algebraic Multigrid (AMG) preconditioners for cardiac mechanics on both structured and unstructured finite element meshes. The mechanical behavior of myocardium can be described by the equations of three-dimensional finite elasticity, which are discretized by finite elements in space and yield the solution of a large scale nonlinear algebraic system. This problem is solved by a Newton-Krylov method, where the solution of the Jacobian linear system is accelerated by BDDC/AMG preconditioners. We thoroughly explore the main parameters of the BDDC preconditioner in order to make the comparison fair. We focus on: the performance of different direct solvers for the local and coarse problems of the BDDC algorithm; the impact of the different choices of BDDC primal degrees of freedom; and the influence of the finite element degree. Scalability tests are performed on Linux clusters up to 1024 processors, and we conclude with a performance study on a realistic electromechanical simulation.

Performance evaluation of communication fabrics for offline parallel electromagnetic transient simulation based on MPI

Offline electromagnetic transient (EMT) simulation is a very time-consuming activity for large-scale and complex power systems. Hydro-Québec (HQ) is involved in the development of EMT simulation tools, one of which can operate both in real-time (RT) and offline. This software heavily relies on parallel processing to achieve high-level performance. However, the offline mode is currently limited as it targets only single system image computers. As the offline mode uses the Message Passing Interface (MPI) standard to implement its parallel processing, porting the offline mode to PC clusters is the logical step to increase the offline simulation capabilities of HQ EMT simulation software.This paper evaluates the performance of different communication fabrics for the execution of offline EMT simulation operating in parallel with MPI. The performance metrics used for this evaluation are first discussed. The evaluated communication fabrics are then presented and tested with an offline simulation of the HQ power transmission system.

A multivariate statistical approach and water quality index for water quality assessment for the Rokel river in Sierra Leone

The main aim of the study was to use multivariate statistical approach to determine the relationship between parameters, identify the factors affecting the quality of water and interpret and group the water quality parameters. Water quality data was collected during two seasons; wet season spanning from June to August 2019 and dry season spanning from February to April 2019. The physiochemical and microbial parameters measured from the sampling process were turbidity, temperature, pH, electric conductivity, total hardness, calcium carbonates, total dissolved solid (TDS), dissolved oxygen (DO), total suspended solids (TSS), iron, nitrate, phosphate, potassium, sulphate, chromium, fluoride, e. coli and coliform. A total of 406 data set were collected and analysed using Principal Component Analysis, water quality index, cluster analysis and analysis of variance (ANOVA). These data sets were tested for sampling adequacy using Kaiser-Meyer-Olkin and Bartlett's Test and the result on the Kaiser-Meyer-Olkin Measure of Sampling Adequacy obtained was 0.615. The analysis yields Five PCs extraction with eigenvalues >1. These components explained 82.628% of the total variance of the entire components. The maximum water quality index 13 which indicated a grade A and can be treated for water supply. The following parameters Chromium 0.39 mg/l, Iron 1.88 mg/l, turbidity 18.66NTU, Phosphates 26.00 mg/l and fluorides 1.75 mg/l exceeded the WHO guidelines for drinking water. The mean values electrical conductivity is 12.26 μS/cm, 31.8 μS/cm for rain and dry seasons respectively., The following parameters Turbidity, Total Dissolved Solid, Total Suspended solids, Iron, Phosphate, Fluoride and Sulphate shows variation with High during the rain and low during the dry season with significant statical difference with a p value < 0.05. Whereas there is difference between the seasonal values of chromium, Nitrate and Potassium. The ANOVA resulted in P-value >0.05 which indicated no statistically significant different for chromium, Nitrate and Potassium. The seasonal variation was corroborated by cluster analysis with two clusters of C1 and C2. The PCs analysis, cluster analysis and ANOVA gave detailed characterization of the source and group correlation amongst the physiochemical and microbial parameters.

A new scheme of plasma control system based on real-time Linux cluster for HL-2M

HL-2M is a medium-sized tokamak constructed by the Southwestern Institute of Physics (SWIP) in China. A new plasma control system (PCS) based on the software framework of DIII-D PCS for HL-2M has been proposed to replace the original loose system. The new hardware system proposed in this paper consists of three computer nodes and peripheral equipment. Data acquisition is completed by a standing server and a reflective memory network that passes back data. The software architecture of DIII-D PCS is generally retained, but some interfaces are added to adapt to the existing system. In addition, the Linux operating system has also been upgraded and optimized so that real-time tasks can achieve better performance. The initial system involves some basic control algorithms satisfying early experiments. The new PCS has been preliminarily verified through simulation and can output control commands as expected in the integrated environment. This paper focuses on two aspects of DIII-D PCS on a new device, i.e., performance and interface adaptation. More efforts will be made to add more algorithms and use the system in real experiments.

Area-based comparison of risk factors and testing rates to improve sexual health care access: cross-sectional population-based study in a Dutch multicultural area

ObjectivesAreas with high sexually transmitted infection (STI) testing rates may not require additional strategies to improve testing. However, it may be necessary to intervene in areas with elevated STI risk,...

A Parallel Solver for FSI Problems with Fictitious Domain Approach

We present and analyze a parallel solver for the solution of fluid structure interaction problems described by a fictitious domain approach. In particular, the fluid is modeled by the non-stationary incompressible Navier–Stokes equations, while the solid evolution is represented by the elasticity equations. The parallel implementation is based on the PETSc library and the solver has been tested in terms of robustness with respect to mesh refinement and weak scalability by running simulations on a Linux cluster.

Evaluation of Parallel Computing on MPI Version PHITS Code

The Message Passing Interface (MPI) technique is an old solution and an improvement on the Monte Carlo N-Particle Transport (MCNP) method’s enormous computational time, which has not been evaluated based on PHITS code—a recently developed Monte Carlo simulation code. We conducted simulations on Varian Clinac iX 6MV phase space data from the IAEA. Venselaar et al.’s method and criteria were used to validate the Monte Carlo simulation. The PC cluster has also been tested in terms of processor count and bch, which stands for unit calculation count per operation. The MPI version PHITS code’s speedup factor and the K-factor, which represent the serial portion of the cluster, were both evaluated. All calculated data met the criteria except δ2, high dose, and high gradient of the beam profile data set. It was very clear that PC clusters with MPI were better than simple nodes up to 70.6%. Additionally, the speedup factor shows a tendency to follow Amdahl’s law. At the same time, the K-factor was saturated by a certain measure. The study concludes by arguing that the cluster has limitations that come from its serial composition. If we consider how improvements in specifications affect simulation time, this cluster system could be more effective.

Trans-Proteomic Pipeline: Robust Mass Spectrometry-Based Proteomics Data Analysis Suite.

The Trans-Proteomic Pipeline (TPP) mass spectrometry data analysis suite has been in continual development and refinement since its first tools, PeptideProphet and ProteinProphet, were published 20 years ago. The current release provides a large complement of tools for spectrum processing, spectrum searching, search validation, abundance computation, protein inference, and more. Many of the tools include machine-learning modeling to extract the most information from data sets and build robust statistical models to compute the probabilities that derived information is correct. Here we present the latest information on the many TPP tools, and how TPP can be deployed on various platforms from personal Windows laptops to Linux clusters and expansive cloud computing environments. We describe tutorials on how to use TPP in a variety of ways and describe synergistic projects that leverage TPP. We conclude with plans for continued development of TPP.

USING SLURM WORKLOAD MANAGER FOR MANAGING SUPERCOMPUTERS AND LINUX CLUSTERS

The article is dedicated to the use of the Slurm Workload Manager for managing supercomputers and Linux clusters and highlighting the importance and advantages of using the Slurm Workload Manager in resource management on multi-user systems. Within the research, existing workload management systems and their limitations were analyzed. Based on this analysis, it was found that Slurm is one of the most widely used and efficient solutions in the field of resource management on multi-user systems. The article provides a detailed examination of the functionality of Slurm, including its core functions such as resource scheduling, task distribution, and system monitoring. Slurm allows users to efficiently utilize computational resources, distribute tasks among cluster nodes, ensure optimal CPU time usage, and control the system load. These features enable high productivity and efficiency in resource utilization. The advantages of Slurm compared to other resource management systems are presented in the article. Slurm is noted for its flexibility and the ability to configure various types of resources, as well as support for different scheduling algorithms. Limitations and challenges associated with using Slurm are also mentioned, providing readers with a comprehensive understanding of its capabilities and potential considerations for implementation. This article will provide readers with a detailed overview of the Slurm Workload Manager, its core functions, advantages, and limitations. With the comprehensive analysis and description of Slurm's core functions, the article will serve as an invaluable source of information for professionals working with large-scale computing clusters and supercomputers. It will also be beneficial for those interested in exploring best practices in resource management on multi-user systems and learning effective strategies for utilizing the Slurm Workload Manager.

An Installation and Model Assessment of the UM, U.K. Earth System Model, in a Linux Cluster

An Installation and Model Assessment of the UM, U.K. Earth System Model, in a Linux Cluster

MAF Translocations Are Enriched in NDMM Patients with Elevated Levels of Circulating Tumor Cells Suggesting a Genetic Basis for Aggressive Disease Course

Introduction A subset of Multiple Myeloma (MM) patients responds poorly to treatment, highlighting the need to understand the pathobiology of high-risk MM. The correlation between aggressive disease and elevated levels of circulating tumor cells (CTCs) has been recognized. We recently identified a subset of high-risk newly diagnosed MM (NDMM) patients based on a transcriptomic classifier derived from patients with high levels of CTC, indicating that CTC levels are a relevant reflection of tumor cell biology. Here, we hypothesized that comparing bone marrow plasma cells (BM PCs) of MM patients with high and low CTC levels will provide an opportunity to identify mechanistic drivers of aggressive disease. Results We first set out to exclude the presence of a circulating aggressive subclone of MM cells in patients with high levels of CTCs. Paired single cell transcriptomes from BM and peripheral blood MM cells of 7 NDMM patients were generated. Analysis of 55,230 CTCs and BM PCs revealed patient specific clustering, but with large transcriptional overlap between individual paired CTCs and BM PCs. Since only 11 genes were significantly upregulated in the BM PCs (P < 0.05) compared to paired CTCs, we excluded the presence of circulating aggressive subclones in patients with high CTC levels. Next, we aimed to identify differences in MM cell pathobiology between patients with high and low levels of CTCs, we generated single cell transcriptomes from 89,092 BM MM cells from 8 NDMM patients with high (≥0.5%) and 14 patients with low (0.004-0.006%) percentages of CTCs. Single cell data integration across all patients led to the identification of 8 distinct PC clusters. Gene set enrichment analysis between both patient groups revealed upregulation of cell cycle pathways in MM cells of patients with high CTC levels. Based on cell cycle analyses an increase in cycling PCs (53% vs 32%, p=0.007) was associated with high CTC levels (Figure 1). Ki67 labeling of BM biopsies validated this finding. Interestingly, proliferation was increased across all transcriptomically-defined plasma cell clusters, suggesting a common cell-intrinsic driver of increased proliferation. To analyze whether the prevalence of genetic lesions previously associated with proliferation was increased in patients with high CTC levels, WGS was performed on the same 22 patients. This revealed an elevated mutation burden and a predilection for MAF translocations, as 50% (4/8) of the patients with high CTC levels carried MAF translocations versus none in the patients with low CTC levels (0/14). We also observed increased transcription of cyclin D2 (CCND2), CCR1 and IntegrinB7 (ITGB7) in patients with high CTC levels. These proliferation or tumor survival genes have been shown to be increased in patients with t(14;16), a translocation also resulting in overexpression of MAF. To validate these findings in a larger patient cohort, clinical, genomic and CTC data were retrieved from the MMRF-CoMMpass database (n=725). Strikingly, 21% of patients with CTC levels above 0.3% showed MAF translocations vs only 3% in patients with CTC levels below 0.3% (p<0.001), solidifying the correlation between MAF translocations and high levels of CTCs in NDMM patients with a high-risk disease profile. Conclusion Single cell RNA sequencing and WGS of MM cells from patients with high and low CTC levels identified a correlation between CTC levels and overrepresentation of MAF translocations in NDMM patients. This finding suggests that MAF target genes and downstream proliferation could be drivers of aggressive disease and might be used for future patient stratification. Figure 1. Based on cell cycle analyses in single cell transcriptomics an increase in cycling PCs was associated with high CTC levels. a) UMAP of cell cycle analysis of 89,902 BM MM cells from 22 patients with high (n=8) and low (n=14) CTC levels. Colors represent cell cycle phase. b) Bar graph representing percentage of cycling cells. Data points are individual patients (high CTC levels, n=8; low CTC levels, n=14). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Pectobacterium carotovorum Phage vB_PcaM_P7_Pc Is a New Member of the Genus Certrevirus.

Pectobacterium carotovorum is an economically important phytopathogen and has been identified as the major causative agent of bacterial soft rot in carrots. Control of this phytopathogen is vital to minimizing carrot harvest losses. As fully efficient control measures to successfully avoid the disease are unavailable, the phage-mediated biocontrol of the pathogen has recently gained scientific attention. In this study, we present a comprehensive characterization of the P. carotovorum phage vB_PcaM_P7_Pc (abbreviated as P7_Pc) that was isolated from infected carrot samples with characteristic soft rot symptoms, which were obtained from storage facilities at market places in Gampaha District, Sri Lanka. P7_Pc is a myovirus, and it exhibits growth characteristics of an exclusively lytic life cycle. It showed visible lysis against four of the tested P. carotovorum strains and one Pectobacterium aroidearum strain. This phage also showed a longer latent period (125 min) than other related phages; however, this did not affect its high phage titter (>1010 PFU/mL). The final assembled genome of P7_Pc is 147,299 bp in length with a G+C content of 50.34%. Of the 298 predicted open reading frames (ORFs) of the genome of P7_Pc, putative functions were assigned to 53 ORFs. Seven tRNA-coding genes were predicted in the genome, while the genome lacked any major genes coding for lysogeny-related products, confirming its virulent nature. The P7_Pc genome shares 96.12% and 95.74% average nucleotide identities with Cronobacter phages CR8 and PBES02, respectively. Phylogenetic and phylogenomic analyses of the genome revealed that P7_Pc clusters well within the clade with the members representing the genus Certrevirus. Currently, there are only 4 characterized Pectobacterium phages (P. atrosepticum phages phiTE and CB7 and Pectobacterium phages DU_PP_I and DU_PP_IV) that are classified under the genus, making the phage P7_Pc the first reported member of the genus isolated using the host bacterium P. carotovorum. The results of this study provide a detailed characterization of the phage P7_Pc, enabling its careful classification into the genus Certrevirus. The knowledge gathered on the phage based on the shared biology of the genus will further aid in the future selection of phage P7_Pc as a biocontrol agent. IMPORTANCE Bacterial soft rot disease, caused by Pectobacterium spp., can lead to significant losses in carrot yields. As current control measures involving the use of chemicals or antibiotics are not recommended in many countries, bacteriophage-mediated biocontrol strategies are being explored for the successful control of these phytopathogens. The successful implementation of such biocontrol strategies relies heavily upon the proper understanding of the growth characteristics and genomic properties of the phage. Further, the selection of taxonomically different phages for the formulation of phage cocktails in biocontrol applications is critical to combat potential bacterial resistance development. This study was conducted to carefully characterize and resolve the phylogenetic placement of the P. carotovorum phage vB_PcaM_P7_Pc by using its biological and genomic properties. Phage P7_Pc has a myovirus morphotype with an exclusively lytic life cycle, and the absence of genes related to lysogeny, toxin production, and antibiotic resistance in its genome confirmed its suitability to be used in environmental applications. Furthermore, P7_Pc is classified under the genus Certrevirus, making it the first reported phage of the genus of the host species, P. carotovorum.

Linear-Scaling Systematic Molecular Fragmentation Approach for Perturbation Theory and Coupled-Cluster Methods.

The coupled-cluster (CC) singles and doubles with perturbative triples [CCSD(T)] method is frequently referred to as the “gold standard” of modern computational chemistry. However, the high computational cost of CCSD(T) [O(N7)], where N is the number of basis functions, limits its applications to small-sized chemical systems. To address this problem, efficient implementations of linear-scaling coupled-cluster methods, which employ the systematic molecular fragmentation (SMF) approach, are reported. In this study, we aim to do the following: (1) To achieve exact linear scaling and to obtain a pure ab initio approach, we revise the handling of nonbonded interactions in the SMF approach, denoted by LSSMF. (2) A new fragmentation algorithm, which yields smaller-sized fragments, that better fits high-level CC methods is introduced. (3) A modified nonbonded fragmentation scheme is proposed to enhance the existent algorithm. Performances of the LSSMF-CC approaches, such as LSSMF-CCSD(T), are compared with their canonical versions for a set of alkane molecules, CnH2n+2 (n = 6–10), which includes 142 molecules. Our results demonstrate that the LSSMF approach introduces negligible errors compared with the canonical methods; mean absolute errors (MAEs) are between 0.20 and 0.59 kcal mol–1 for LSSMF(3,1)-CCSD(T). For a larger alkanes set (L12), CnH2n+2 (n = 50–70), the performance of LSSMF for the second-order perturbation theory (MP2) is investigated. For the L12 set, various bonded and nonbonded levels are considered. Our results demonstrate that the combination of bonded level 6 with nonbonded level 2, LSSMF(6,2), provides very accurate results for the MP2 method with a MAE value of 0.32 kcal mol–1. The LSSMF(6,2) approach yields more than a 26-fold reduction in errors compared with LSSMF(3,1). Hence, we obtain substantial improvements over the original SMF approach. To illustrate the efficiency and applicability of the LSSMF-CCSD(T) approach, we consider an alkane molecule with 10,004 atoms. For this molecule, the LSSMF(3,1)-CCSD(T)/cc-pVTZ energy computation, on a Linux cluster with 100 nodes, 4 cores, and 5 GB of memory provided to each node, is performed just in ∼24 h. As a second test, we consider a biomolecular complex (PDB code: 1GLA), which includes 10,488 atoms, to assess the efficiency of the LSSMF approach. The LSSMF(3,1)-FNO–CCSD(T)/cc-pVTZ energy computation is completed in ∼7 days for the biomolecular complex. Hence, our results demonstrate that the LSSMF-CC approaches are very efficient. Overall, we conclude the following: (1) The LSSMF(m, n)-CCSD(T) methods can be reliably used for large-scale chemical systems, where the canonical methods are not computationally affordable. (2) The accuracy of bonded level 3 is not satisfactory for large chemical systems. (3) For high-accuracy studies, bonded level 5 (or higher) and nonbonded level 2 should be employed.

A variational splitting of high-order linear multistep methods for heat transfer and advection–diffusion parabolic problems

The main result of this paper is the generalization of the concept of variational splitting proposed by Behnoudfar et al. (2018) into higher-order time-stepping schemes. The key novelty of the technique proposed here is the following: when using the isogeometric finite elements, one can factorize the matrix of the linear system and obtain the linear complexity. This matrix has the form M+ηK, where M is the mass matrix, K is the stiffness matrix. Following the technique of Behnoudfar et al. (2018), and factorizing M+ηK one would get the additional error of order η2. We propose the technique to couple the possibility of factorization of M+ηK with the higher-order time-stepping schemes and preserve this higher order. Thus, we introduce a variational splitting for implicit, linear multistep methods of order s for parabolic partial differential equations. Our technique exploits the tensor-product structure of the discretization in space (mesh and basis functions) to derive an update strategy with a linear cost regarding the total number of degrees of freedom for multi-dimensional problems. As an example, we consider two popular methods: Adams–Moulton (AM) and backward differentiation formulae (BDF). We derive the corresponding coefficients for AM and BDF methods. We present a C++ implementation of the time-integration schemes, targeting shared-memory Linux clusters. We present numerical results for the heat transfer problem and advection–diffusion problem. We also discuss the limitations of the method and possible extensions overcoming this limitation by using our method as a preconditioner for an iterative solver.

Interpreting alignment-free sequence comparison: what makes a score a good score?

Alignment-free methods are alternatives to alignment-based methods when searching sequence data sets. The output from an alignment-free sequence comparison is a similarity score, the interpretation of which is not straightforward. We propose objective functions to interpret and calibrate outputs from alignment-free searches, noting that different objective functions are necessary for different biological contexts. This leads to advantages: visualising and comparing score distributions, including those from true positives, may be a relatively simple method to gain insight into the performance of different metrics. Using an empirical approach with both DNA and protein sequences, we characterise different similarity score distributions generated under different parameters. In particular, we demonstrate how sequence length can affect the scores. We show that scores of true positive sequence pairs may correlate significantly with their mean length; and even if the correlation is weak, the relative difference in length of the sequence pair may significantly reduce the effectiveness of alignment-free metrics. Importantly, we show how objective functions can be used with test data to accurately estimate the probability of true positives. This can significantly increase the utility of alignment-free approaches. Finally, we have developed a general-purpose software tool called KAST for use in high-throughput workflows on Linux clusters.

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations.

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.