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作者： Simone Lauterbach Hannah Dienhart Jan Range Stephan Malzacher Jan-Dirk Spöring Dörte Rother Maria Filipa Pinto Pedro Martins Colton E. Lagerman Andreas S. Bommarius Amalie Vang Høst John M. Woodley Sandile Ngubane Tukayi Kudanga Frank T. Bergmann Johann M. Rohwer Dorothea Iglezakis Andreas Weidemann Ulrike Wittig Carsten Kettner Neil Swainston Santiago Schnell Jürgen Pleiss

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://*** . less

关键词： programming language Python Statistical Calculation Enzymatic Assay Data integration Biocatalysis Enzymes

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A Study on Atomics-based Integer Sum Reduction in HIP on AMD GPU 22

A Study on Atomics-based Integer Sum Reduction in HIP on AMD...

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Workshop Proceedings of the 51st International Conference on Parallel Processing

作者： Zheming Jin Jeffrey Vetter Oak Ridge National Laboratory United States of America Oak Ridge National Laboratory USA

ISBN: (纸本)9781450394451

Integer sum reduction is a primitive operation commonly used in scientific computing. Implementing a parallel reduction on a GPU often involves concurrent memory accesses using atomic operations and synchronization of work-items in a work-group. For a better understanding of these operations, we redesigned micro-kernels in the HIP programming language to measure the time of atomic operations over global memory, the cost of barrier synchronization, and reduction within a work-group to shared local memory using one atomic addition per work-item on a compute unit in an AMD MI100 GPU. Then, we describe the implementations of the reduction kernels with vectorized memory accesses, parameterized workload sizes, and vendor's library APIs. Our experimental results show that 1) there is a performance tradeoff between the cost of barrier synchronization and the amount of parallelism from atomic operations over shared local memory when we increase the size of a work-group. 2) a reduction kernel with vectorized memory accesses and vector data types is approximately 3% faster for the large problem size than the kernels written with the vendor's library APIs. 3) the compiler needs to assist the hardware processor with data dependency resolution at the level of instruction set architecture. 4) the power consumption of the kernel execution on the GPU fluctuates between 277 Watts and 301 Watts and the dynamic power of other GPU activities is at most 31 Watts.

关键词： programming language Parallel reduction GPU

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Impact of programming languages on Energy Consumption for Sorting Algorithms 50th

Impact of Programming Languages on Energy Consumption for So...

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50th Annual Convention of the Computer-Society-of-India (CSI) on Digital Life

作者： Chandra, Tej Bahadur Verma, Pushpak Dwivedi, Anuj Kumar MATS Univ Sch Informat Technol Raipur Chhattisgarh India Govt Vijay Bhushan Singh Deo Girls Degree Coll Jashpur 496331 Chhattisgarh India

ISBN: (纸本)9789811088483;9789811088476

In today's scenario, this world is moving rapidly toward the global warming. Various experiments are performed, to concentrate more on the energy efficiency. One way to achieve this is by implementing the sorting algorithms in such a programming language which consumes least amount of energy which is our current area of research in this paper. In this study, our main goal is to find such a programming language which consumes least amount of energy and contributes to green computing. In our experiment, we implemented different sorting algorithms in different programming languages in order to find the most power-efficient language.

关键词： programming language Sorting algorithms Power consumption Joulemeter

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EzMechanism: an automated tool to propose catalytic mechanisms of enzyme reactions

EzMechanism: an automated tool to propose catalytic mechanis...

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作者： Antonio J. Ribeiro Ioannis G. Riziotis Jonathan D. Tyzack Neera Borkakoti Janet M. Thornton

Over the years, hundreds of enzyme reaction mechanisms have been studied using experimental and simulation methods. This rich literature on biological catalysis is now ripe for use as the foundation of new knowledge-based approaches to investigate enzyme mechanisms. Here, we present a tool able to automatically infer mechanistic paths for a given three-dimensional active site and enzyme reaction, based on a set of catalytic rules compiled from the Mechanism and Catalytic Site Atlas, a database of enzyme mechanisms. EzMechanism (pronounced as ‘Easy’ Mechanism) is available to everyone through a web user interface. When studying a mechanism, EzMechanism facilitates and improves the generation of hypotheses, by making sure that relevant information is considered, as derived from the literature on both related and unrelated enzymes. We validated EzMechanism on a set of 62 enzymes and have identified paths for further improvement, including the need for additional and more generic catalytic *** the years, hundreds of enzyme reaction mechanisms have been studied using experimental and simulation methods. This rich literature on biological catalysis is now ripe for use as the foundation of new knowledge-based approaches to investigate enzyme mechanisms. Here, we present a tool able to automatically infer mechanistic paths for a given three-dimensional active site and enzyme reaction, based on a set of catalytic rules compiled from the Mechanism and Catalytic Site Atlas, a database of enzyme mechanisms. EzMechanism (pronounced as ‘Easy’ Mechanism) is available to everyone through a web user interface. When studying a mechanism, EzMechanism facilitates and improves the generation of hypotheses, by making sure that relevant information is considered, as derived from the literature on both related and unrelated enzymes. We validated EzMechanism on a set of 62 enzymes and have identified paths for further improvement, including the need for additional and more generic ca

关键词： Python programming language Cytoscape Computational models Software Protein function predictions Enzymes

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CD4+ T Cell Epitope Identification from Complex Parasite Antigen Mixtures

CD4+ T Cell Epitope Identification from Complex Parasite Ant...

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作者： Miguel Álvaro-Benito Friederike Ebner Miriam Bertazzon Eliot Morrison

Antigen complexity represents a major challenge for scoring CD4+ T cell immunogenicity, a key hallmark of immunity and with great potential to improve vaccine development. In this chapter, we provide a comprehensive picture of a pipeline that can be applied to virtually any complex antigen to overcome different limitations. Antigens are characterized by Mass Spectrometry to determine the available protein sources and their abundances. A reconstituted in vitro antigen processing system is applied along with bioinformatics tools to prioritize the list of candidates. Finally, the immunogenicity of candidate peptides is validated ex vivo using PBMCs from HLA-typed individuals. This protocol compiles the essential information for executing the whole pipeline while focusing on the candidate epitope prioritizing scheme. less

关键词： Spectroscopy Mass Spectrometry Cell And Tissue Culture Isotope Labeling SDS-PAGE Proteomics Peptide Identification programming language Flow Cytometry DNA Ligation Long-term Culture Co-culture Chromatography FPLC FACS Homo sapiens Antigen presentation MHC II CD4+ T cell reactivity Ascaris spp. parasites Excretory-secretory products (ES) Reconstitution in vitro antigen processing Complex antigen mixtures Anti-human CD40 Anti-human CD28 Anti-biotin Anti-CD3 Anti-HLA-DR

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Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS

Inferring cellular and molecular processes in single-cell da...

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作者： Jeanette A. Johnson Ashley P. Tsang Jacob T. Mitchell David L. Zhou Julia Bowden Emily Davis-Marcisak Thomas Sherman Ted Liefeld Melanie Loth Loyal A. Goff Jacquelyn W. Zimmerman Ben Kinny-Köster Elizabeth M. Jaffee Pablo Tamayo Jill P. Mesirov Michael Reich Elana J. Fertig Genevieve L. Stein-O’Brien

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suite of computational tools that implement NMF and provide methods for accurate and clear biological interpretation and analysis. A generalized discussion of NMF covering its benefits, limitations and open questions is followed by four procedures for the Bayesian NMF algorithm Coordinated Gene Activity across Pattern Subsets (CoGAPS). Each procedure will demonstrate NMF analysis to quantify cell state transitions in a public domain single-cell RNA-sequencing dataset. The first demonstrates PyCoGAPS, our new Python implementation that enhances runtime for large datasets, and the second allows its deployment in Docker. The third procedure steps through the same single-cell NMF analysis using our R CoGAPS interface. The fourth introduces a beginner-friendly CoGAPS platform using GenePattern Notebook, aimed at users with a working conceptual knowledge of data analysis but without a basic proficiency in the R or Python programming language. We also constructed a user-facing website to serve as a central repository for information and instructional materials about CoGAPS and its application programming interfaces. The expected timing to setup the packages and conduct a test run is around 15 min, and an additional 30 min to conduct analyses on a precomputed result. The expected runtime on the user’s desired dataset can vary from hours to days depending on factors such as dataset size or input ***-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we

关键词： Machine Learning Python Statistical Calculation Single-cell RNA-seq Data analysis programming language Seurat Apis Software Computational platforms and environments Bayesian inference

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Manipulating and Basic Analysis of Tabular Metagenomics Datasets Using R

Manipulating and Basic Analysis of Tabular Metagenomics Data...

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作者： Alex Coleman Martin Callaghan

Handling and manipulating tabular datasets is a critical step in every metagenomics analysis pipeline. The R statistical programming language offers a variety of versatile tools for working with tabular data that allow for the development of computationally efficient and reproducible workflows. Here we outline the basics of the R programming language and showcase a number of tools for data manipulation and basic analysis of metagenomics datasets. less

关键词： programming language Data analysis Metagenomics Data handling Reproducible research Data manipulation

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Evaluate the Understandability of Raku's Syntax

World Scientific Research Journal

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World Scientific Research Journal 2022年第2期8卷 366-379页

作者： Zhiyuan He Xuejing Li

Raku is a 'Practical Extraction And Reporting language', which combines the features of C, sed, awk, shell scripting and many other programming languages, which can simplify simple tasks without losing the ability to deal with difficult problems, but at the same time it is a niche programming language without much People know and use it. This paper aims to evaluate the syntax of Raku in two particular aspects, including manipulating numbers and working with files. The understandability of Raku's syntax by programmers, who have mastered python before, was verified by doing a think‐aloud test and semistructured interview. Comparisons between Raku, Perl5 and Python were added to deepen the study to check that whether Raku is more suitable for programmers who are supporters of previous versions of Perl. Results of the research showed that Raku's syntax in manipulating numbers and working with files is hard and easy respectively for students, who have learned Python, to understand. Also, Perl5 users indeed have some advantages in understanding the syntax of Raku, while the diversity of Raku also made this language is friendly to Python users.

关键词： Raku programming language Python Perl

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Peripheral Nervous System Responses to Food Stimuli:

Peripheral Nervous System Responses to Food Stimuli:

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作者： Maelle Moranges Marc Plantevit Moustafa Bensafi

In the field of food, as in other fields, the measurement of emotional responses to food and their sensory properties is a major challenge. In the present protocol, we propose a step-by-step procedure that allows a physiological description of odors, aromas, and their hedonic properties. The method rooted in subgroup discovery belongs to the field of data science and especially data mining. It is still little used in the field of food and is based on a descriptive modeling of emotions on the basis of human physiological responses.

关键词： Data Mining Python programming language Emotions Pleasantness Odors Aromas Food stimuli Subgroup discovery

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Array-Based Multiplex and High-Throughput Serology Assays

Array-Based Multiplex and High-Throughput Serology Assays

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作者： Jennie Olofsson Ceke Hellström Eni Andersson Jamil Yousef Lovisa Skoglund Ronald Sjöberg Anna Månberg Peter Nilsson Elisa Pin

The detection of antibody responses using serological tests provides means to diagnose infections, follow disease transmission, and monitor vaccination responses. The coronavirus disease 2019 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, highlighted the need for rapid development of robust and reliable serological tests to follow disease spreading. Moreover, the rise of SARS-CoV-2 variants emphasized the need to monitor their transmission and prevalence in the population. For this reason, multiplex and flexible serological assays are needed to allow for rapid inclusion of antigens representing new variants as soon as they appear. In this chapter, we describe the generation and application of a multiplex serological test, based on bead array technology, to detect anti-SARS-CoV-2 antibodies in a high-throughput manner, using only a few microliters of sample. This method is currently expanding to include a multi-disease antigen panel that will allow parallel detection of antibodies towards several infectious agents. less

关键词： Protein Array Data analysis Vaccination Cross-linking PCR programming language SARS-CoV-2 Serology Serum Antibody Multiplex Plasma High-throughput Anti-COVID Anti-human

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