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At least 19 recordsLinked to original sources

PubMed2026

PanDelos-plus: A parallel algorithm for computing sequence homology in pangenomic analysis.

The identification of homologous gene families across multiple genomes is a central task in bacterial pangenomics traditionally requiring computationally demanding all-against-all comparisons. PanDelos addresses this challenge with an alignment-free and parameter-free approach based on k-mer profiles, combining high speed, ease of use, and competitive accuracy with state-of-the-art methods. However, the increasing availability of genomic data requires tools that can scale efficiently to larger datasets. To address this need, we present PanDelos-plus, a fully parallel, gene-centric redesign of PanDelos. The algorithm parallelizes the most computationally intensive phases (Best Hit detection and Bidirectional Best Hit extraction) through data decomposition and a thread pool strategy, while employing lightweight data structures to reduce memory usage. Benchmarks on synthetic datasets show that PanDelos-plus achieves up to 14x faster execution and reduces memory usage by up to 96%, while maintaining consistency with the original algorithm. These improvements allow the PanDelos methodology to be applied to population-scale comparative genomics, thus enabling more precise characterisation of pangenome structure and dynamics. PanDelos-plus is available at github.com/synbionics/PanDelos-plus.

Journal Article↗

PubMed2025

Parallel algorithms for phylogenetic inference under a structured coalescent approximation.

While advances in molecular epidemiology and computational modeling have enhanced our capacity to track pathogen evolution, the accurate reconstruction of spatiotemporal transmission dynamics remains essential for developing epidemic preparedness frameworks and implementing outbreak response measures. Structured coalescent models offer a phylogeographic framework by restricting lineage coalescence events to geographically proximate host populations. Although the Bayesian structured coalescent approximation (BASTA) provides a tractable approach, contemporary phylogeographic analyses involving dozens of geographic localities and hundreds to thousands of viral genomes substantially exceed the computational capacity of existing implementations. The BASTA likelihood scales cubically with deme count and quadratically with sequence count due to matrix exponentiation and pairwise coalescent probability calculations. Here, we introduce a comprehensive algorithmic restructuring of the structured coalescent likelihood that eliminates redundancies, optimizes memory access, and exposes parallelization opportunities. Our approach reorganizes computations along three dimensions: (i) independent calculation of deme-transition probability matrices across time intervals; (ii) simultaneous evaluation of partial likelihood vectors within temporal slices; and (iii) concurrent aggregation of coalescent probabilities. Algorithmic restructuring cuts average coalescent likelihood computation by 7-8 fold, and parallelization further boosts performance to 10-26 fold, enabling joint phylogeographic analyses of dengue virus across 10 South American countries and H5N1 avian influenza across 20 Eurasian regions to finish in a fraction of prior time. This computational efficiency also enables comparison between backward-in-time structured coalescent approximations and forward-in-time phylogeographic methods, revealing that the former provides appropriately conservative posterior estimates, particularly at intermediate phylogenetic depths. We integrate our implementation into the popular BEAST X and BEAGLE software packages, with an accompanying interface in BEAUti X to easily set up the analyses, providing researchers with an accessible and scalable tool for real-time phylogeographic surveillance of rapidly evolving pathogens.

Journal Article↗

PubMed2026

Accelerating minimap2 for whole-genome alignment.

SUMMARY: Recent advances in long-read sequencing and genome assembly techniques have enabled the generation of high-quality assemblies, often comprising megabase-scale sequences that span entire chromosomes. This results in longer but fewer sequences per genome, which affects the parallelization efficiency of whole-genome alignment tools. Current methods that assign one thread per query sequence now face suboptimal CPU use and longer runtimes because the processing of fewer sequences leaves many threads idle. We present mm2-plus, a fast and efficient method for whole-genome alignment, built upon the commonly used minimap2 aligner. Our improvements include a fine-grained parallel chaining algorithm and a fast method for differentiating primary and secondary chains. These optimizations accelerate the alignment of human, plant, and primate genomes by 1.6× to 7.2× without compromising accuracy. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/at-cg/mm2-plus and https://doi.org/10.5281/zenodo.18220923.

Sequence Alignment↗

PubMed2026

Bit-reproducible parallel phylogenetic tree inference.

MOTIVATION: Phylogenetic trees describe the evolutionary history among biological species based on their genomic data. Maximum likelihood (ML) based phylogenetic inference tools search for the tree and evolutionary model that best explain the observed genomic data. Given the independence of likelihood score calculations between different genomic sites, parallel computation is commonly deployed. This is followed by a parallel summation over the per-site scores to obtain the overall likelihood score of the tree. However, basic arithmetic operations on IEEE 754 floating-point numbers, such as addition and multiplication, inherently introduce rounding errors. Consequently, the order by which floating-point operations are executed affects the exact resulting likelihood value since these operations are not associative. Moreover, parallel reduction algorithms in numerical codes re-associate operations as a function of the core count and cluster network topology, inducing different round-off errors. These low-level deviations can cause heuristic searches to diverge and induce high-level result discrepancies (e.g. yield topologically distinct phylogenies). This effect has also been observed in multiple scientific fields beyond phylogenetics. RESULTS: We observe that varying the degree of parallelism results in diverging phylogenetic tree searches (high-level results) for over 31% out of 10 179 empirical datasets. More importantly, 8% of these diverging datasets yield trees that are statistically significantly worse than the best-known ML tree for the dataset (AU-test, P < .05). To alleviate this, we develop a variant of the widely used phylogenetic inference tool RAxML-NG, which does yield bit-reproducible results under varying core-counts, with a slowdown of only 0%-12.7% (median 0.8%) on up to 768 cores. For this, we introduce the ReproRed reduction algorithm, which yields bit-identical results under varying core-counts, by maintaining a fixed operation order that is independent of the communication pattern. ReproRed is thus applicable to all associative reduction operations-in contrast to competitors, which are confined to summation. Our ReproRed reduction algorithm only exchanges the theoretical minimum number of messages, overlaps communication with computation, and utilizes fast base-cases for local reductions. ReproRed is able to all-reduce (via a subsequent broadcast) 4.1×106 operands across 48-768 cores in 19.7-48.61 μs, thereby exhibiting a slowdown of 13%-93% over a non-reproducible all-reduce algorithm. ReproRed outperforms the state-of-the-art reproducible all-reduction algorithm ReproBLAS (offers summation only) beyond 10 000 elements per core. In summary, we re-assess non-reproducibility in parallel phylogenetic inference, present the first bit-reproducible parallel phylogenetic inference tool, as well as introduce a general algorithm and open-source code for conducting reproducible associative parallel reduction operations. AVAILABILITY AND IMPLEMENTATION: ReproRed: https://doi.org/10.5281/zenodo.15004918 (LGPL)-Reproducible RAxML-NG version https://doi.org/10.5281/zenodo.15017407 (GPL).

Phylogeny↗

PubMed1979

An iterative algorithm for the separation of action potential sequences.

Various iterative algorithms for separation of superimposed event sequences were designed, and their efficiency examined through simulation studies. It has been found that a double parallel-serial algorithm improved markedly the efficiency of the filtration process. For the same probability of detection of the event series to be extracted, the probability of 'impurity' events dropped by roughly 0.10, as compared to the non-iterative fixed window width algorithm. Conclusions are drawn regarding separation of motor unit action potential sequences from the total electromyogram.

Action Potentials↗

PubMed2024

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information.

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Glycopeptides↗

PubMed2026

MethylModes: computationally efficient detection of multimodal distributions in DNA methylation data.

SUMMARY: MethylModes is an R package and Shiny application to identify multimodal distributions in human DNA methylation at individual CpG sites. Multimodal distributions, which can be the result of nearby genetic variation, environmental exposures, or assay artifacts, are susceptible to confounding and important to identify for methylation analysis. MethylModes is easily incorporated into existing quality control pipelines of array-based DNA methylation data. The underlying algorithm uses kernel smoothing of probe-level data to locate the number and location of peaks. The algorithm can be parallelized across probes for efficient implementation at genome-scale. We provide a case study implementation of MethylModes in the Health and Retirement Study as well as the Airwave Health Monitoring Study. AVAILABILITY AND IMPLEMENTATION: MethylModes is available on GitHub at https://github.com/lutiffan/methylModes as an R package wrapping an R Shiny application. We include a toy dataset to validate installation. The codebase is also published on Zenodo at https://doi.org/10.5281/zenodo.17448517.

DNA Methylation↗

PubMedDate not supplied

Structure analysis and classification of cervical cells using a processing system based on TV.

This paper presents preliminary results of a cell classification experiment using a new approach for feature extraction. The algorithm takes into account the special requirements of a fast parallel processing system (processor-oriented algorithms). A cell image is described by several hundred features derived from the nucleus only. The most significant features with respect to classification are determined by statistical analysis. Applying principal axis transform, a new feature set is computed, reduced considerably in dimensions. The data base (1,925 cell images of Papanicolaou-stained cervical specimens) was divided into a training set (963 images) and a test set (962 images). The classification results of the test set show that the recognition rate for the two-class problem (normal, suspicious) is better than 91%, using only ten morphologic features.

Cervix Mucus↗

PubMed1979

Utilization of cross-plane rays for three-dimensional reconstruction by filtered back-projection.

Present popular computed tomography (CT) algorithms reconstruct an object from the ray measurements lying on a set of parallel planes. This paper presents an algorithm that can also utilize "cross-plane" rays (i.e., rays that cross through many planes) to reconstruct the object. In this reconstruction algorithm, the ray measurements are grouped into two-dimensional projections, filtered, and stored. The filtered projections can then be back-projected onto a three-dimensional matrix or any plane through the three-dimensional volume. General theoretical aspects are presented and then applied to the special case in which ray measurements have been made in all directions. The algorithm is tested using computer-generated data. Expressions for the noise power spectrum and the variance in the reconstruction are derived. It is shown that the noise-to-signal ratio per detected photon for this reconstruction method is close to a theoretical limit, as it also is for normal CT. The ability to use ray measurements that cross many planes is especially useful in emission CT, where order-of-magnitude improvements in image quality per unit dose can be achieved.

Computers↗

PubMed1979

Application of optimized parallel processing digital computers and numerical approximation methods to the ultra high-speed three-dimensional reconstruction of the intact thorax.

In order to achieve the computational capability to carry out many thousands of cross-sectional reconstructions, necessary to support a prototype high temporal and spatial resolution cylindrical scanning multiaxial tomographic unit, a series of design, software simulation, and fabrication studies is underway to develop a special-purpose high-speed reconstruction computer. This processor will rely upon integrated circuit arithmetic components of advanced design, and highly parallel architecture to execute X-ray based transaxial reconstruction algorithms at the rate of hundreds of cross sections/sec.

Computers↗

PubMed1979

Whole-body single-photon emission computed tomography using dual, large-field-of-view scintillation cameras.

A whole-body single-photon emission computed tomography system (SPECT) consisting of two large-field-of-view scintillation cameras mounted on a rotatable gantry, a minicomputer and a display station has been designed, constructed and evaluated. In its usual mode of operation, eleven contiguous transverse sections, each 12.5 or 25 mm thick, are reconstructed from projection data acquired during a single, continuous 360 degree rotation lasting from 2 to 22 min. A generalised filtered and weighted backprojection algorithm is used to reconstruct data obtained with conventional parallel-hole collimators in the case of body scanning, or with specially designed fan beam collimators in the case of centrally positioned organs. A simple, yet effective, correction is used to compensate for the effects of gamma ray attenuation within the patient. In addition to providing transverse section images, the system is capable of simultaneous acquisition of opposed conventional scintigrams, the reconstruction of longitudinal section images, and the acquisition of gated cardiac transverse sections. Resolutions in the reconstructed images are typically 15 mm for body scans and 11 mm for brain scans, with only slight variations in sensitivity and resolution within the image. Phantoms and clinical data demonstrate that the SPECT system generates high quality section images while maintaining most of the flexibility of normal scintillation cameras, with the added advantage of dual heads.

Tomography, Emission-Computed↗

PubMed1979

Data collection for cross-sectional image reconstruction by a moving ring of positron annihilation detectors.

A ring of positron annihilation detectors capable of two independent motions in the plane of the ring is considered. It can rotate around its center, and the whole ring may move so that its center traces a circular path. Provided certain parameters are chosen according to given formulas, data collected by such a detector ring can be reorganized (rebinned), in a computationally very inexpensive fashion, so that the data items in each bin are measurements along parallel lines spaced at small equal intervals. Efficient high resolution reconstruction algorithms that assume such data organization can therefore be applied to data collected collected by a moving positron ring detector. The method is demonstrated on a realistic example.

Computers↗

PubMed1979

A computerized rotating laminar radionuclide camera.

We have constructed a radionuclide camera that embodies a unique detector-collimator concept and provides a radically new approach to imaging. The heart of the instrument is a linear array of semiconductor detectors separated by thin tungsten plates that confine the field of view of each detector to one dimension. This collimator design has a higher collection efficiency than the standard parallel-hole collimator but cannot directly produce a two-dimensional image. When multiple measurements are taken as the array rotates through 180 degrees, a computerized image restoration algorithm can then produce two-dimensional images with resolution determined by the width of the detectors. A small prototype camera has produced images with resolution superior to conventional Anger cameras.

Computers↗

PubMed2025

PRISM: privacy-preserving rare disease analysis using fully homomorphic encryption.

MOTIVATION: Rare diseases affect millions of people worldwide, yet their genomic foundations remain poorly understood due to limited patient data and strict privacy regulations, such as the General Data Protection Regulation (GDPR) (https://gdpr.eu/tag/gdpr/) in March 2025. These restrictions can hinder the collaborative analysis of genomic data necessary for uncovering disease-causing variants. RESULTS: We present PRISM, a novel privacy-preserving framework based on fully homomorphic encryption (FHE) that facilitates rare disease variant analysis across multiple institutions without exposing sensitive genomic information. To address the challenges of centralized trust, PRISM is built upon a Threshold FHE scheme. This approach decentralizes key management across participating institutions and ensures no single entity can unilaterally decrypt sensitive data. Our method filters disease-causing variants under recessive, dominant, and de novo inheritance models entirely on encrypted data. We propose two algorithmic variants: a multiplication-intensive (MUL-IN) approach and an addition-intensive (ADD-IN) approach. The ADD-IN algorithms minimize the number of costly multiplication operations, enabling up to a 17× improvement in runtime for recessive/dominant filtering and 22× for de novo filtering, compared to MUL-IN methods. While ADD-IN produces larger ciphertexts, efficient parallelization via SIMD and multithreading allows it to handle millions of variants in reasonable time. To the best of our knowledge, this is the first study that utilizes FHE for privacy-preserving rare disease analysis across multiple inheritance models, demonstrating its practicality and scalability in a single-cloud setting. AVAILABILITY AND IMPLEMENTATION: The source code and the data used in this work can be found in https://github.com/mdppml/PRISM.git.

Computer Security↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

A novel method for across-chromosome phasing without relative data.

MOTIVATION: Across-chromosome phasing identifies which haplotypes of different chromosomes come from the same parent. This differs from within-chromosome phasing, which uses linkage disequilibrium patterns to determine which alleles were co-inherited within each chromosome but does not match haplotypes across different chromosomes. While across-chromosome phasing can be conducted using genotypes from parents or close relatives, current methods perform poorly for samples of unrelated individuals. Here, we introduce a novel approach for across-chromosome phasing that employs a window-based SNP-similarity metric, eliminating the need for data from close relatives or detection of identical-by-descent haplotypes. RESULTS: Using UK Biobank offspring with both parents genotyped as a gold standard, we evaluated the performance of our method by phasing the offspring without using parental data. In genomic data with no within-chromosome phase errors, our algorithm achieved a mean across-chromosome phasing accuracy of 95%, with 53% of individuals phased perfectly. When data was pre-phased computationally using a standard within-chromosome phasing algorithm, mean accuracy for across-chromosome phasing dropped to 83.1%. Thus, our method is limited primarily by the accuracy of within-chromosome phasing accuracy and can approach near-perfect across-chromosome phasing accuracy as within-chromosome phasing accuracy improves. AVAILABILITY AND IMPLEMENTATION: The implementation was executed within a multi-node computational environment of University of Colorado Boulder Research Computing (Blanca Cluster: https://www.colorado.edu/rc/resources/blanca), employing parallelization techniques in the C programming language. The source code has been made publicly accessible online at https://github.com/emmanuelsapin/AcrossChromosomesPhasing, thereby facilitating reproducibility of the results for researchers with authorized access to the UK Biobank dataset.

Algorithms↗

PubMed2026

Integrating NECTIN4 Amplification With Membranous Nectin-4 Expression to Develop a Scoring System for Predicting Enfortumab Vedotin Response in Urothelial Carcinoma.

PURPOSE: Enfortumab vedotin (EV) is standard therapy for metastatic urothelial carcinoma (mUC), yet the predictive relevance of NECTIN4 expression-especially membranous versus cytoplasmic-remains unclear. Here, we sought to extend previous findings on NECTIN4 gene amplification in parallel with a systematic subcellular evaluation of NECTIN4 expression. EXPERIMENTAL DESIGN: We retrospectively analyzed 179 EV-treated mUC patients. NECTIN4 amplification was assessed by FISH and NECTIN4 protein levels by IHC. A four-tier membranous scoring algorithm (0,1+,2+,3+) adapted from CAP HER2 gastric guidelines was benchmarked against H-score. We integrated amplification status with membranous staining to refine predictive stratification and compared associations with objective response rate (ORR) to EV-301 data. RESULTS: Combining membranous and cytoplasmic compartments resulted in a median composite H-score of 260 (78.2% ≥150), closely matching NECTIN4 expression prevalence reported in EV-301 (median 250; 82.6% ≥ 150). A ≥150 cut-off enriched for EV responders in both cohorts; in EV-301 with ORR of 45.8% vs. 20% (P = 0.001). High membranous expression based on the scoring (2+/3+) predicted response (ORR 55.1% vs. 25.5%; P < 0.001), with longer PFS (7.1 vs. 2.9 months; HR 0.45) and OS (12.3 vs. 6.9 months; HR 0.57), whereas cytoplasmic expression lacked predictive value. NECTIN4-amplified tumors showed particularly favorable outcomes (PFS 12.2 months; OS 30.1 months). An integrated three-tier model-amplified, non-amplified/high-membranous, and non-amplified/low-membranous-yielded ORRs of 77.2%, 42.9%, and 26.1% and separated survival outcomes. CONCLUSIONS: Our NECTIN4 scoring system integrating NECTIN4 amplification with membranous NECTIN4 expression accurately predicts outcomes, supporting combined genomic and membranous assessment as complementary biomarkers for optimizing EV selection.

Journal Article↗

PubMed1979

Rapid analysis of hematology image data: the ADC-500 preprocessor.

A sequential, pipeline processor (that we have named the ADC-500 preprocessor) has been developed which scene segments the three color image data from the ADC-500 optics one image element at a time, groups together image elements from each object in the scene and extracts features from each object. The processing occurs at television frame rates, requiring 16.7 msec to process the entire image. This speed was instrumental in allowing the ADC-500 automated differential analyzer to perform routine 500-cell differentials. The preprocessor also contains hardware which simplifies compilation of the three color histograms. The segmentation algorithms implemented in the preprocessor are multicolor extensions of the classical monochrome density histogram threshold method. For most cell image analysis tasks, a sequential pipeline processor of this type should be more economical and as fast or faster than a parallel processor.

Blood Cells↗