23 papers · ranked by Valyu relevance
Wenxing Hu, Haotian Zhang, Jake Gagnon, Zhengyu Ouyang + 4 more
The rise of large-scale single-cell RNA-seq data has introduced challenges in data processing due to its slow speed. Leveraging advancements in GPU computing ecosystems, such as CUPY, and building on the NVIDIA genomics team’s rapid-singlecell (RSC) package, we developed scaleSC, a GPU-accelerated solution for…
Marta Moreno, Ricardo Vilaça, Pedro G. Ferreira
Background Gene expression studies are an important tool in biological and biomedical research. The signal carried in expression profiles helps derive signatures for the prediction, diagnosis and prognosis of different diseases. Data science and specifically machine learning have many applications in gene expression…
Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys
Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing…
Yuanchao Zhang, Deanne M. Taylor
In single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially due to significant improvements on single-cell isolation and massively parallel sequencing technologies. However, computational methods have not scaled to the same order, presenting analytical challenges to the…
Lizhen Shi, Zhong Wang
The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions…
Gunnar Brataas, Antonio Martini, Geir Kjetil Hanssen, Georg Ræder
Eliciting scalability requirements during agile software development is complicated and poorly described in previous research. This article presents a lightweight artifact for eliciting scalability requirements during agile software development: the ScrumScale model. The ScrumScale model is a simple spreadsheet. The…
N. Robinson, Joseph Hamman, Ryan Abernathey
Thousands of climate scientists have been eagerly awaiting the data from the sixth iteration of the Climate Model Intercomparison Project (CMIP), which is now becoming available online [1]. The data, at a volume that is expected to exceed 20 Petabytes, represent the most detailed predictions ever made about the future…
Gohta Aihara, Kalen Clifton, Mayling Chen, Zhuoyan Li + 6 more
Spatial omics technologies enable high-throughput molecular profiling of single cells or small groups of cells while preserving their spatial relationships within tissue sections (). This high-throughput profiling demands computational analysis to leverage both molecular and spatial information in extracting relevant…
Benjamin Murray, Eric Kerfoot, Liyuan Chen, Jie Deng + 16 more
'Mark S. Graham' 'Carole H. Sudre' 'Erika Molteni' 'Liane S. Canas' 'Michela Antonelli' 'Kerstin Klaser' 'Alessia Visconti' 'Alexander Hammers' 'Andrew T. Chan' 'Paul W. Franks' 'Richard Davies' 'Jonathan Wolf' 'Tim D. Spector' 'Claire J. Steves' 'Marc Modat' 'Sebastien Ourselin'] The Covid Symptom Study, a…
Parashar Dhapola, Johan Rodhe, Rasmus Olofzon, Thomas Bonald + 3 more
The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the computational requirements to efficiently handle growing datasets. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for…
Sven Van Poucke, Zhongheng Zhang, Martin Schmitz, Milan Vukicevic + 4 more
'Margot Vander Laenen' 'Leo Anthony Celi' 'Cathy De Deyne' 'Tudor Groza'] With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and…
Natalie Perlin, Joel Zysman, Ben P. Kirtman
—The concept of scalability analysis of numerical parallel applications has been revisited, with the specific goals defined for the performance estimation of research applications. A series of Community Climate Model System (CCSM) numerical simulations were used to test the several MPI implementations, determine…
Sascha Herzinger, Valentin Grouès, Wei Gu, Venkata Satagopam + 3 more
In the field of translational research, we are facing an ever-growing amount of preclinical, clinical, OMICS, and mobile-sensor data that should be considered as a whole to understand the bigger picture of underlying diseases and biological processes. A platform that is able to store, link, and analyze the different…
Gonzalo Gómez-Sánchez, Aaron Call, Xavier Teruel, Lorena Alonso + 4 more
'Ignasi Morán' 'Miguel Ángel Pérez-Martín' 'David Torrents' 'Josep Ll. Berral'] Abstract. The use of large-scale supercomputing architectures is a hard requirement for scientific computing Big-Data applications. An example is genomics analytics, where millions of data transformations and tests per patient need to be…
Authors not listed
—With the increasing importance of distributed scientific workflows, there is a critical need to ensure Quality of Service (QoS) constraints, such as minimizing time or limiting execution to resource subsets. However, the unpredictable nature of workflow behavior, even with similar configurations, makes it difficult to…
Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel + 3 more
'Dinh-Phong Nguyen' 'Youcef Sebiat' 'Dian Sun'] Results and Discussion: SCALPEL3 horizontal scalability allows handling large tasks quicker than the existing infrastructure while it has comparable performance when using only a few executors. SCALPEL3 provides a sharp interactive control of data processing through…
Authors not listed
Mass spectrometry (MS) is a cornerstone technology in modern molecular biology, powering diverse applications across proteomics, metabolomics, lipidomics, glycomics, and beyond. As the field continues to evolve, rapid advancements in instrumentation, acquisition strategies, machine learning, and scalable computing have…
Authors not listed
The integration of artificial intelligence technologies into pharmaceutical research is crucial for gaining an early understanding of molecular properties, thereby facilitating successful drug design. Constructing a machine learning (ML) model however, requires knowledge spanning from data preprocessing and feature…
Y. C. Tay
A computer system has multiple components, possibly a mix of both hardware and software. It may be a processor architecture on a chip, or a software suite that supports some application in the cloud. In our context, analytical modeling essentially refers to the formulation of equations to describe the performance of…
Eftychia Eva Kontou, Axel Walter, Oliver Alka, Julianus Pfeuffer + 5 more
Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for…
Andrew Simmonett, Bernard Brooks, Thomas Darden
Evaluation of noncovalent electrostatic interactions is the dominant bottleneck in classical molecular dynamics simulations, and evaluation of Coulombic matrix elements similarly limits quantum mechanical self consistent field calculations. These difficulties are a result of the Coulomb operator’s slow decay, which…
Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, Álvaro Fernández-Galiana + 2 more
Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardisation, and the…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…