Alignment Tool Research Articles

RepeatsDB in 2025: expanding annotations of structured tandem repeats proteins on AlphaFoldDB.

RepeatsDB (URL: https://repeatsdb.org) stands as a key resource for the classification and annotation of Structured Tandem Repeat Proteins (STRPs), incorporating data from both the Protein Data Bank (PDB) and AlphaFoldDB. This latest release features substantial advancements, including annotations for over 34000 unique protein sequences from >2000 organisms, representing a fifteenfold increase in coverage. Leveraging state-of-the-art structural alignment tools, RepeatsDB now offers faster and more precise detection of STRPs across both experimental and predicted structures. Key improvements also include a redesigned user interface and enhanced web server, providing an intuitive browsing experience with improved data searchability and accessibility. A new statistics page allows users to explore database metrics based on repeat classifications, while API enhancements support scalability to manage the growing volume of data. These advancements not only refine the understanding of STRPs but also streamline annotation processes, further strengthening RepeatsDB's role in advancing our understanding of STRP functions.

Evaluating Sequence Alignment Tools for Antimicrobial Resistance Gene Detection in Assembly Graphs

Antimicrobial resistance (AMR) is an escalating global health threat, often driven by the horizontal gene transfer (HGT) of resistance genes. Detecting AMR genes and understanding their genomic context within bacterial populations is crucial for mitigating the spread of resistance. In this study, we evaluate the performance of three sequence alignment tools—Bandage, SPAligner, and GraphAligner—in identifying AMR gene sequences from assembly and de Bruijn graphs, which are commonly used in microbial genome assembly. Efficiently identifying these genes allows for the detection of neighboring genetic elements and possible HGT events, contributing to a deeper understanding of AMR dissemination. We compare the performance of the tools both qualitatively and quantitatively, analyzing the precision, computational efficiency, and accuracy in detecting AMR-related sequences. Our analysis reveals that Bandage offers the most precise and efficient identification of AMR gene sequences, followed by GraphAligner and SPAligner. The comparison includes evaluating the similarity of paths returned by each tool and measuring output accuracy using a modified edit distance metric. These results highlight Bandage’s potential for contributing to the accurate identification and study of AMR genes in bacterial populations, offering important insights into resistance mechanisms and potential targets for mitigating AMR spread.

A deep transfer learning model for online monitoring of surface roughness in milling with variable parameters

Surface roughness is crucial for the functional and aesthetic properties of mechanical components and must be carefully controlled during machining. However, predicting it under varying machining parameters is challenging due to limited experimental data and fluctuating factors like tool wear and vibration. This study develops a deep transfer learning model that incorporates the correlation alignment method and tool wear to enhance model generalization and reduce data acquisition costs. It utilizes multi-sensor data and the ResNet18 with a convolutional block attention module (CBAM-ResNet) to extract features with improved generalization and accuracy for monitoring milled surface roughness under varying conditions. The performance of the model is evaluated from different perspectives. First, the proposed model achieves high accuracy with fewer than 500 experimental samples from the target domain by using the CORAL module in the CBAM-ResNet model. This demonstrates the model's strong generalization capability by minimizing second-order statistical discrepancies between different datasets. Second, ablation experiments reveal a significant reduction in test error when incorporating CORAL and tool wear, highlighting their contributions to improved model generalization. Integrating tool wear information significantly reduces test errors across various transfer conditions, as it reflects changes in cutting force, vibration, and built-up edge formation. Third, comparisons with existing deep transfer models further emphasize the advantages of the proposed approach in improving model generalization. In summary, the proposed surface roughness model, which incorporates tool wear and multi-sensor signal features as inputs and employs feature transfer and CBAM-ResNet, demonstrates superior generalization and accuracy across various machining parameters.

BoReMi: Bokeh-based jupyter-interface for registering spatio-molecular data to related microscopy images.

Spatio-molecular data and microscopy images provide complementary information, essential to study structure and function of spatially organised multicellular systems such as healthy or diseased tissues. However, aligning these two types of data can be challenging due to distortions and differences in resolution, orientation, and position. Manual registration is tedious but may be necessary for challenging samples as well as for the generation of ground-truth data sets that enable benchmarking of existing and emerging automated alignment tools. To make the process of manual registration more convenient, efficient, and integrated, we created BoReMi, a python-based, Jupyter-integrated, visual tool that offers all the relevant functionalities for aligning and registering spatio-molecular data and associated microscopy images. We showcase BoReMi's utility using publicly available data and images and make BoReMi as well as an interactive demo available on GitHub.

The Study of the Balancing Process for Starting Rotors in Heavy-Duty Vehicles: An Industrial Application

In the heavy-duty vehicle industry, unbalance in the armature is one of the most common problems affecting starters’ performance and durability. This research presents a comprehensive study to improve the balancing process for starting rotors in heavy-duty vehicles. The complete manufacturing process of armatures was analyzed to understand the contribution of assembly processes to unbalancing. The analysis revealed that the primary factor leading to high unbalance in these parts is the misalignment of conductors within the armature winding. During assembly, these conductors experience axial movements, resulting in non-uniform mass distribution and causing unbalanced values ranging from 150 to 350 g·mm. These values surpass the permissible limit, making rectification during the balancing process at the end of the assembly impossible. Consequently, a novel alignment tool was designed to address this issue, significantly reducing the effect and achieving the maximum allowable unbalance of 100 g·mm. This allowed the balancing machine used in the process to correct the initial unbalance of the reinforcements in a single work cycle, improving operation efficiency by about 15%.

Revisiting the functional annotation of TriTryp using sequence similarity tools

Trypanosomatids are the causative agents of deadly diseases in humans and livestock. Given the high phylogenetic distance of trypanosomatids from model organisms, these organisms have ample unannotated genes. Manual functional annotation is time-consuming, highlighting the importance of automated functional annotation tools. The development of automated functional tools is a hot research topic, and multiple tools have been developed for the task. PANNZER2 is an automated functional annotation tool that merely relies on the sequence similarity of the query to the annotated proteins. We tried PANNZER2 on Trypanosoma brucei, the most studied organism among trypanosomatids, to see if it could improve our knowledge of the functions of the genes.Even with the availability of automated annotation tools like InterPro2GO in databases such as TriTrypDB, PANNZER2 has made surprisingly confident predictions for some hypothetical proteins in T. brucei. In this study, we identify gaps in such annotations because of not employing pairwise sequence alignment tools in TriTrypDB's automated annotation process. Our findings demonstrate that even the use of stringent cutoffs can successfully annotate a significant number of proteins. Additionally, we discovered that adjusting the open reading frames in certain genes leads to sequences with increased sequence signature coverage—characterized by the length covered by at least one sequence signature—compared to the original sequences. This enhanced sequence signature coverage suggests these genomic fragments could be pseudogenes. To facilitate further exploration, we developed a script to help identify potential pseudogenes within an organism's genome, offering researchers a new tool for genomic analysis and understanding. We extended all our analysis to Trypanosoma cruzi and Leishmania major to assess the impact of this approach across different species.Our study demonstrates that by utilizing pairwise sequence similarity alignment, even with stringent cutoffs, we can attribute 2986, 3953, and 3798 new GO terms to the genomes of T. brucei, T. cruzi, and L. major. Additionally, we found that 210, 239, and 29 genes exhibit increased sequence signature coverage following frame correction, suggesting the presence of pseudogenes.

Clinical Utility of Qualitative Change of Direction Movement Assessment in ACL Injury Risk Evaluation.

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Development of a Predictive Model Based on the Alignment Tool in the Early Stages of Projects: The Case of Saudi Arabia Infrastructure Projects

The construction industry plays a substantial role in shaping the economies of many countries. Construction management faces various challenges that can lead to project failures, particularly in infrastructure projects struggling to meet cost and time requirements. Inadequate project planning and the intricate nature of construction projects can cause participants’ project goals to not align. It is crucial to address these challenges early in the planning stages to ensure project success. This research involved investigating previous studies to understand current practices for improving infrastructure project planning and selecting the best pre-project planning tool. Infrastructure projects in the Saudi construction industry are used as a case study. A questionnaire was prepared based on essential alignment issues affecting team alignment during pre-project planning. Participants rated the level of agreement with alignment issues and the overall success of a project they worked on. The study utilized descriptive and inferential analysis techniques to assess infrastructure project success rates and develop a predictive model driven by the alignment tool. Multiple linear regression techniques were used during the model’s development, and validation and reliability outputs were obtained. By evaluating all relevant stakeholders, the model generates a score to facilitate the pre-project planning process, increasing the likelihood of project success. The study found that the model’s predictive accuracy was 94%. This research is significant in creating a predictive model applicable to infrastructure projects, enhancing project management practices by enabling project teams to evaluate project progress, identify projects in need of corrective action, and ultimately improve project performance, leading to cost and time savings.

Optimizing Sample Preparation for Destructive Testing in Resistance Spot Welding

Abstract The integrity and reliability of resistance spot welding, a crucial process in various manufacturing industries, are significantly influenced by the quality of sample preparation. This study focuses on advancing the methodologies and practices in the preparation of samples for resistance spot welding destructive tests, aiming to improve the precision and repeatability of the results. We discuss comprehensive approaches encompassing material selection, surface treatment, dimensional accuracy, and alignment procedures, emphasizing the importance of meticulous handling and preparation techniques, A significant focus is placed on the utilization of sophisticated alignment and measurement tools to enhance the consistency of the welding area subjected to destructive testing. our study demonstrates a significant improvement in the reliability and accuracy of welding machine calibration, ultimately contributing to the overall quality of the welding process. By integrating these refined processes, the study highlights a significant improvement in the reliability of welding tests, contributing to enhanced welding quality and performance in practical applications. Our findings underscore the critical role of detailed and standardized sample preparation in achieving accurate and reliable resistance spot welding destructive test outcomes, providing valuable insights for both industrial applications and further research in welding technology.

PheSA: An Open-Source Tool for Pharmacophore-Enhanced Shape Alignment.

PheSA is an open-source pharmacophore- and shape-based screening and molecular alignment tool that is fully open-source as part of OpenChemLib. Supporting standard ligand-based screening, flexible refinement of alignments, and receptor-guided shape docking, PheSA is a very flexible tool and can be used for different use cases in structure-based drug design. We present the algorithm and different benchmark studies that investigate the screening performance and also the quality of the generated alignments and the pose prediction performance of the receptor-guided PheSA algorithm. An important finding is the effect of the type of similarity metric used for measuring screening enrichment (symmetric Tanimoto versus asymmetric Tversky), whereby we could observe improved enrichment rates by using Tversky. PheSA exhibits enrichments on the DUD-E that are on par with commercial methods.

ViewR: Architectural-Scale Multi-User Mixed Reality With Mobile Head-Mounted Displays.

The emergence of mobile head-mounted displays with robust "inside-out" markerless tracking and video-passthrough permits the creation of novel mixed reality (MR) experiences in which architectural spaces of arbitrary size can be transformed into immersive multi-user visualisation arenas. Here we outline ViewR, an open-source framework for rapidly constructing and deploying architectural-scale multi-user MR experiences. ViewR includes tools for rapid alignment of real and virtual worlds, tracking loss detection and recovery, user trajectory visualisation and world state synchronisation between users with persistence across sessions. ViewR also provides control over the blending of the real and the virtual, specification of site-specific blending zones, and video-passthrough avatars, allowing users to see and interact with one another directly. Using ViewR, we explore the transformation of large architectural structures into immersive arenas by creating a range of experiences in various locations, with a particular focus on architectural affordances such as mezzanines, stairs, gangways and elevators. Our tests reveal that ViewR allows for experiences that would not be possible with pure virtual reality, and indicate that, with certain strategies for recovering from tracking errors, it is possible to construct large scale multi-user MR experiences using contemporary consumer virtual reality head-mounted displays.

The primate-specific presence of interferon regulatory factor-5 pseudogene 1.

Interferon regulatory factor 5 (IRF5) is a key transcription factor in inflammatory and immune responses, with its dysregulation linked to autoimmune diseases. Using bioinformatic approaches, including Basic Local Alignment Search Tool (BLAST) for sequence similarity searches, BLAST-Like Alignment Tool (BLAT) for genome-wide alignments, and several phylogenetics software, such as Multiple Alignment using Fast Fourier Transform (MAFFT), for phylogenetic analyses, we characterized the structure, origin, and evolutionary history of the human IRF5 pseudogene 1 (IRF5P1). Our analyses reveal that IRF5P1 is a chimeric processed pseudogene containing sequences derived from multiple sources, including IRF5-like sequences from disparate organisms. We find that IRF5P1 is specific to higher primates, likely originating through an ancient retroviral integration event approximately 60 million years ago. Interestingly, IRF5P1 resides within the triple QxxK/R motif-containing (TRIQK) gene, and its antisense strand is predominantly expressed as part of the TRIQK pre-messenger RNA (mRNA). Analysis of publicly available RNA-seq data suggests potential expression of antisense IRF5P1 RNA. We hypothesize that this antisense RNA may regulate IRF5 expression through complementary binding to IRF5 mRNA, with human genetic variants potentially modulating this interaction. The conservation of IRF5P1 in the primate lineage suggests its positive effects on primate evolution and innate immunity. This study highlights the importance of investigating pseudogenes and their potential regulatory roles in shaping lineage-specific immune adaptations.

An FPGA-based hardware accelerator supporting sensitive sequence homology filtering with profile hidden Markov models

BackgroundSequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). Here, we describe an FPGA hardware accelerator, called HAVAC, that targets a key bottleneck step (SSV) in the analysis pipeline of the popular pHMM alignment tool, HMMER.ResultsThe HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} $3000 Xilinx Alveo U50 FPGA accelerator card, ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 227× faster than the optimized SSV implementation in nhmmer. Accounting for PCI-e data transfer data processing, HAVAC is 65× faster than nhmmer’s SSV with one thread and 35× faster than nhmmer with four threads, and uses ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 31% the energy of a traditional high end Intel CPU.ConclusionsHAVAC demonstrates the potential offered by FPGA hardware accelerators to produce dramatic speed gains in sequence annotation and related bioinformatics applications. Because these computations are performed on a co-processor, the host CPU remains free to simultaneously compute other aspects of the analysis pipeline.

DNA barcoding, inter-specific and inter-generic variation studies on South Indian scaly tree ferns (Cyathea sp.pl.) using chloroplast rbcL gene

DNA barcoding is an effective identification tool for tree ferns with heteromorphic generations with morphologically simple gametophytic phase. A complete reference dataset which includes coverage of the target local flora is necessary for accurate identification. Three different Cyathea sp.pl. were investigated to test the utility of plastid DNA barcode regions rbcL with the intention of developing an identification system for native pteridophytes. In addition, the inter-specific and inter-generic variations among the Cyathea sp.pl. were also focused. BLAST analysis revealed the similar rbcL sequences related to C. nilgirensis Holttum, C. gigantea (Wallich ex Hook. f.) Holttum and C. crinita (Hook.) Copel and a sum of 143 sequences viz., Cyathea sp.pl. (121), Gymnosphaera sp.pl.(4), Sphaeropteris sp.pl. (1) and Alsophila sp.pl. (17). The sequences of 143 plants were retrieved from GenBank in FASTA format. The sequences were aligned using multiple sequence alignment tool MUSCLE. The inter-specific and inter-generic distance percentage were calculated using Maximum Likelihood, Minimum Evolution, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) and Neighbor-Joining method. The analyses were constructed using MEGA X software. The rbcL gene provided sequence variation with its strong resolving power. This study demonstrates the overall effectiveness of DNA barcodes for species identification of tree fern genus Cyathea in the pteridophyte flora of Southern Western Ghats.

Chromosome-Scale Genome Assembly of the Sheep-Biting Louse Bovicola ovis Using Nanopore Sequencing Data and Pore-C Analysis.

Bovicola ovis, commonly known as the sheep-biting louse, is an ectoparasite that adversely affects the sheep industry. Sheep louse infestation lowers the quality of products, including wool and leather, causing a loss of approximately AUD 123M per annum in Australia alone. The lack of a high-quality genome assembly for the sheep-biting louse, as well as any closely related livestock lice, has hindered the development of louse research and management control tools. In this study, we present the assembly of B. ovis with a genome size of ~123 Mbp based on a nanopore long-read sequencing library and Illumina RNA sequencing, complemented with a chromosome-level scaffolding using the Pore-C multiway chromatin contact dataset. Combining multiple alignment and gene prediction tools, a comprehensive annotation on the assembled B. ovis genome was conducted and recalled 11,810 genes as well as other genomic features including orf, ssr, rRNA and tRNA. A manual curation using alignment with the available closely related louse species, Pediculus humanus, increased the number of annotated genes to 16,024. Overall, this study reported critical genetic resources and biological insights for the advancement of sheep louse research and the development of sustainable control strategies in the sheep industry.

Using a Centroid-based approach for a reliable identification of morels (Morchella spp.): A case study for food authentication.

Food fraud is a problematic yet common phenomenon in the food industry. It impacts numerous sectors, including the market of edible mushrooms. Morel mushrooms are prized worldwide for their culinary and medicinal use. They represent a taxonomically complex group in which food fraud has already been reported. Among the methods to evaluate food fraud, some rely on comparisons of genetic sequences obtained from a sample to existing databases. However, the quality and usefulness of the results are limited by the type of comparison tool and the quality of the database used. The Centroid-based approach is applied by SmartGene in a proprietary artificial intelligence-based method for the generation of automatically curated reference databases that can be further expert curated. In this study, using sequences of the ribosomal internal transcribed spacer (ITS) of the genus Morchella (true morels), we compared this approach to the traditional pairwise alignment tool using two other databases: UNITE and Mycobank (MLST). The Centroid-based approach using an expert-curated database was more performant for the identification of 53 representative ITS sequences corresponding to validated species (83% accuracy, compared to 36% and 47% accuracy for UNITE and MLST, respectively). The Centroid method also revealed an inaccurate taxonomic annotation for sequences of commercial cultivars submitted to public databases. Combined with the web-based commercial software IDNS® available at Smartgene, the Centroid-based approach constitutes a valuable tool to ensure the quality of morel products on the market for actors of the food industry. PRACTICAL APPLICATION: The Centroid-based approach can be used by agri-food actors who need to identify true morels down to the species level without any prior taxonomical knowledge. These include routine laboratories of the food industry, food distributors, and public surveillance agencies. This is a reliable method that requires minimal skills and resources, therefore being particularly adapted for nonspecialists.

Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.

Unravelling reference bias in ancient DNA datasets.

The alignment of sequencing reads is a critical step in the characterization of ancient genomes. However, reference bias and spurious mappings pose a significant challenge, particularly as cutting-edge wet lab methods generate datasets that push the boundaries of alignment tools. Reference bias occurs when reference alleles are favoured over alternative alleles during mapping, whereas spurious mappings stem from either contamination or when endogenous reads fail to align to their correct position. Previous work has shown that these phenomena are correlated with read length but a more thorough investigation of reference bias and spurious mappings for ancient DNA has been lacking. Here, we use a range of empirical and simulated palaeogenomic datasets to investigate the impacts of mapping tools, quality thresholds, and reference genome on mismatch rates across read lengths. For these analyses, we introduce AMBER, a new bioinformatics tool for assessing the quality of ancient DNA mapping directly from BAM-files and informing on reference bias, read length cut-offs and reference selection. AMBER rapidly and simultaneously computes the sequence read mapping bias in the form of the mismatch rates per read length, cytosine deamination profiles at both CpG and non-CpG sites, fragment length distributions, and genomic breadth and depth of coverage. Using AMBER, we find that mapping algorithms and quality threshold choices dictate reference bias and rates of spurious alignment at different read lengths in a predictable manner, suggesting that optimized mapping parameters for each read length will be a key step in alleviating reference bias and spurious mappings. AMBER is available for noncommercial use on GitHub (https://github.com/tvandervalk/AMBER.git). Scripts used to generate and analyse simulated datasets are available on Github (https://github.com/sdolenz/refbias_scripts).

TomoPyUI: a user-friendly tool for rapid tomography alignment and reconstruction.

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data (i.e. organizing data/metadata, applying image filters etc.) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI, a user interface for the well known tomography data processing package TomoPy. This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI, along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI, and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

Anatomical Reference of the Femur after Distal Resection Is Reliable for Rotational Alignment in Total Knee Arthroplasty.

The rotational alignment of the femoral component in total knee arthroplasty (TKA) is considered an important factor, but it is still difficult to assess intraoperatively. This study was conducted to identify anatomical parameters for femoral rotational alignment. A total of 204 patients who underwent primary TKA between 2015 and 2019 were enrolled. The femoral lateral (FLAP) and femoral medial anteroposterior (FMAP) lengths were measured as the widest lengths in the anteroposterior (AP) axis after distal femoral resection. The difference between FLAP and FMAP was defined as dFAP. The concordance correlation coefficient (CCC) was assessed for agreement between the cTEA-PCA and the value of femoral rotation using the linear regression analysis equation. HKA, FLAP, FMAP, and dFAP were significantly associated with femoral rotational alignment. The prediction equation combining the novel intraoperative anatomical references showed improved association with rotational alignment. If dFAP was 6.0 mm, the femoral rotation angle was calculated as 4.9° using this univariate regression equation. The CCC was 0.483, indicating moderate agreement. The dFAP showed an association with distal femoral rotational alignment. A 6 mm dFAP could be a reference for around 5° of femoral rotation. The equation developed in this study may be a reliable tool for intraoperative distal femoral rotational alignment.