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56 results for “Product engineering”
Raw data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief
<p>This repository consists of the raw western blot, microscopy and mass spectrometry data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief and associated with the article '<a href="https://www.ncbi.nlm.nih.gov/pubmed/31805379">Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production</a>' published in the journal Metabolic Engineering (see DOI: 10.1016/j.ymben.2019.11.007). </p> <p>The western blot raw file is associated with Figure 1a and 1b of the Data in Brief manuscript.</p> <p>The confocal microscopy raw image files (x3) are associated with Figure 1c of the Data in Brief manuscript.</p> <p>The mass spectrometry files are the raw data that refers to the samples presented in Figure 5 of the Data in Brief manuscript. Files are labelled as in the Data in Brief and Metabolic Engineering manuscripts. The file name structures is as follows;</p> <p>CHO-Controlpoolai</p> <p>Where 'a' represents replicate 'a' of three biological replicates and 'i' refers to mass spectrometry technical analysis 1 of 3 technical analyses of each replicate (thus for each cell pool or line there are three biological replicates that are each analysed in triplicate such that there are 9 raw mass spectrometry files for each cell pool or line).</p> <p>All the mass spectrometry files are found in the compressed (zip) file named mass_spectrometry_raw_files_archive.zip</p>
ValRun: GMP-grade Manufacturing and Quality Control of a Non-Virally engineered Advanced Therapy Medicinal Product for Personalized Treatment of Age-Related Macular Degeneration
<p><strong>VaLRun: </strong></p> <p><strong>Raw data of "GMP-grade Manufacturing and Quality Control of a Non-Virally engineered Advanced Therapy Medicinal Product for Personalized Treatment of Age-Related Macular Degeneration"</strong></p> <p>(Excel-, pdf-, GraphPad-files, mp4 videos and a READ-ME text file)</p> <p>The introduction of new therapeutics requires validation of Good Manufacturing Practice (GMP)-grade manufacturing including suitable quality controls. This is challenging for Advanced Therapy Medicinal Products (ATMP) with personalized batches. We have developed a person-alized, cell-based gene therapy to treat age-related macular degeneration and established a vali-dation strategy of the GMP-grade manufacture for the ATMP; manufacturing and quality control were challenging due to a low cell number, batch-to-batch variability and short production duration. Instead of patient iris pigment epithelial cells, human donor tissue was used to produce the transfected cell product (“tIPE”). We implemented an extended validation of 104 tIPE productions. Procedure, operators and devices have been validated and qualified by determining cell number, viability, extracellular DNA, sterility, duration, temperature and volume. Transfected autologous cells were transplanted to rabbits verifying feasibility of the treatment. A container has been engineered to insure a safe transport from the production to the surgery site. Criteria for successful validation and qualification were based on tIPE’s Critical Quality Attributes and Process Parameters, its manufacture and release criteria. The validated process and qualified operators are essential to bring the ATMP into clinic and offer a general strategy for the transfer to other manufacture centers and personalized ATMPs.</p>
Supplementary data for Model-driven engineering of Cutaneotrichosporon oleaginosus ATCC 20509 for improved microbial oil production
<p>Supplementary data corresponding to manuscript named Model-driven engineering of <em>Cutaneotrichosporon oleaginosus</em> ATCC 20509 for improved microbial oil production. </p> <p>The Supplementary material document contains supplementary figures and tables. The content of the figures and tables are indicated below. </p> <ul> <li>Figure S1. Plasmid map of pUC57NAT containing pGpd, nourseothricin acyltransferase gene and tGpd.</li> <li>Figure S2. Plasmid maps of overexpression targets containing TEF1α promoter, ATP-citrate lyase gene, TEF1α terminator, TPI1 promoter, Acetyl-CoA carboxylase gene, TPI1, YAT1 promoter, threonine synthase gene, YAT1 terminator and ENO1 promoter, hydroxymethylglutaryl-CoA synthase gene, ENO1 terminator.</li> <li>Table S2. Nucleotide sequences of promoters, genes, and terminators from <em>C. oleaginosus.</em></li> <li>Figure S3. Calibration curve of glycerol for calculating the glycerol concentration of medium.</li> <li>Figure S4. Volcano plots displaying differentially expressed genes and fold change (log2) in expression levels in WT, Δ9 and Δ12 strains at low lipid accumulation vs high lipid accumulation conditions.</li> <li>Figure S5. Flux distribution graphs of selected reactions for overexpression in C. oleaginosus.</li> <li>Figure S6. Colony PCR products were run on 1 % agarose gel. The colony PCR was performed for WT, ACL, ACC and TS transformants.</li> <li>Table S4. qPCR outputs, CT: The threshold cycle.</li> <li>Table S5. Fatty acid profile of C. oleaginosus grown at minimal medium with or without supplement (biotin, thiamine, threonine, serine, and aspartate) at 96h.</li> <li>Table S6. Lipid content, dry cell weight, and lipid weight of WT, ACL, ACC, TS, and HMGS <em>C. oleaginosus</em> at various C/N ratio minimal medium.</li> <li>Table S7. Fatty acid profile of WT, ACL, ACC, HMGS, and TS grown at C/N30, 120, 175, 200, and 300 minimal medium at 96h.</li> <li>Figure S7. Quadratic regression analysis on lipid accumulation, biomass and lipid content of wild-type, ACL, ACC, and TS C. oleaginosus at C/N 30, 120, 175, 200, 300.</li> <li>Table S8. Regression equations, statistics of regression equations for lipid content, biomass, and lipid content of wild-type, ACL, ACC, and TS.</li> <li>Table S9. Calculated optimum C/N ratios and responses (lipid content, biomass, and total lipid) by using built regression models for wild-type, ACL, ACC, and TS.</li> </ul> <p>Authors: </p> <p>Zeynep Efsun Duman-Özdamar<sup>a,b,c</sup>, Mattijs K. Julsing<sup>c</sup>, Janine A.C. Verbokkem<sup>c</sup>, Emil Wolbert<sup>c</sup>, Vitor A.P. Martins dos Santos<sup>a,b,d</sup>, Jeroen Hugenholtz<sup>e,f</sup>, Maria Suarez-Diez<sup>b*</sup></p> <p><sup>a</sup>Bioprocess Engineering, Wageningen University & Research, 6708 PB, Wageningen, the Netherlands</p> <p><sup>b</sup>Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE, Wageningen, the Netherlands</p> <p><sup>c</sup>Wageningen Food & Biobased Research, Wageningen University & Research, 6708 WE, Wageningen, The Netherlands</p> <p><sup>d</sup>LifeGlimmer GmbH, Berlin, 12163, Germany</p> <p><sup>e</sup>Faculty of Science Swammerdam Institute for Life Sciences, University of Amsterdam, 1090 GE Amsterdam, The Netherlands</p> <p><sup>f</sup>NoPalm Ingredients BV, 6709 PA Wageningen, The Netherlands</p>
A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines
<p>The dataset used for evaluating the hybrid feature location technique presented in the paper: "A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines". This enables reproducibility, evaluation, and comparison of our study.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Dataset" contains for each subject system used:</p> <p>(i) the artificial variants and their configurations;</p> <p>(ii) the ECCO repository containing the traces;</p> <p>(iii) the ground truth and composed variants;</p> <p>(iv) the metrics results.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Scenarios" contains for each subject system used:</p> <p>(i) the videos recorded from exercising features on GUI.</p>
FABIAN: a daily product of Fractional Austral-summer Blue Ice over ANtarctica during 2000-2021 based on MODIS imagery using Google Earth Engine
<p>This is a supplementary data set for FABIAN: a daily product of Fractional Austral-summer Blue Ice over ANtarctica during<br> 2000{2021 based on MODIS imagery using Google Earth Engine</p> <p>The files include:</p> <p>(1) Snow spectra modelled by TARTES, a two-stream radiative transfer model for light in snow (Libois et al., 2013).</p> <p>(2) Spectra extracted from MODIS, using AUTO-EM.</p> <p>(3) Endmember selection results, including ESS, EMC, and AMUSES.</p> <p>The other hyperspectral data from field measurements can be acquired by contact the original authors.</p> <p>Libois, Q., Picard, G., France, J., Arnaud, L., Dumont, M., Carmagnola, C., King, M., 2013. Influence of grain shape on light penetration in snow. The Cryosphere 7, 1803-1818.</p>
Cell-free synthesis of infective phages from in vitro assembled phage genomes for efficient phage engineering and production of large phage libraries
<p>Upload of relevant sequencing data for the paper "<strong>Cell-free synthesis of infective phages from <em>in vitro</em> assembled phage genomes for efficient phage engineering and production of large phage libraries"</strong></p>
Achieving Energy Efficiency with a Software Product Line Engineering Approach
<p>This is a Live PhD. Thesis Presentation; Also playable at:</p><p><a href="https://youtu.be/yaYEoj4S3pc">https://youtu.be/yaYEoj4S3pc</a></p><p>Please access and cite the published PhD. Thesis book: <a href="https://doi.org/10.5281/zenodo.10007921 ">https://doi.org/10.5281/zenodo.10007921 </a></p><ul><li><strong>Author</strong>: Daniel-Jesus Munoz</li><li><strong>Directors</strong>: Lidia Fuentes and Monica Pinto.</li></ul><p>CAOSD group, Universidad de Málaga, Andalucía Tech, Spain </p><p>Post-defense presentation recorded at Universität Ulm in 2023.</p><p>Energy-aware software design can energy-aware software design can reduce total energy consumption by 30-90%. However, the different ways of measuring energy consumption in real time are very complex. Energy readings are provided as the total energy consumption in joules or the rate of energy consumption in watts. For battery-powered battery-powered devices, joules per task is a more interesting metric, while watts per task is more commonly used for battery-powered devices. per task is more used for devices directly connected to power. The usual approach to modelling and storing approach to modelling and storing power consumption readings is to describe them as a characteristic of individual components, such as monetary cost. individual components, such as the monetary cost of a hardware component. However, the energy consumption values have many interactions between components, which makes it difficult to describe them with individual, static energy values. This makes it difficult to describe them in terms of individual, static energy values. Instead, we can store and energy information can be stored and populated in collaborative databases. The IEA and Datarade offer free databases with energy consumption data. free databases with energy consumption data for energy efficiency and sustainability analysis. Without However, the databases are not scalable for highly configurable systems because of the curse of the dimension. Our work focuses on Industry 4.0, specifically on Cyber-Physical Systems (acronym CPS), which are characterised by their high configurability and adaptability, presenting a large number of alternatives and a colossal number of alternatives and a colossal number of different systems in operation. This is known as the This is known as the search/solution space, the size of which is the set of all possible points that satisfy an optimisation problem. optimisation problem. Partially known solution spaces are a common problem in many fields, such as computer engineering, machine learning, artificial intelligence and goal-oriented optimisation. engineering, machine learning, artificial intelligence and goal-oriented optimisation. The Constraint Satisfaction Problems (CSP) are mathematical problems defined as a set of objects whose state must satisfy a set of constraints. set of objects whose state must satisfy a set of constraints. Variability Models (acronym VMs) are tree-like structures used to represent the commonalities and differences of a CPS. Numerical Features (NFs) can be used in VMs to represent quantitative properties of the system, but they can be used to represent quantitative properties of the system, but most tools do not support NFs. In addition, NFs increase the size of the VM, NFs increase the size of the solution space by multiplying it by its domain size, which makes large solution spaces colossal. large solution spaces into colossal ones. Quality Models (QMs) are tree structures that are used to determine which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a project. which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a system. system. ISO/IEC 25010 is the most popular QM formalisation, which groups QAs into eight different types. The Automated reasoning is the automation of formal logical reasoning to compute different types of information about system models. Examples are providing a VM or QM to a reasoning tool, and calculating the size of the reasoning tool, and calculating the size of the solution space, checking the satisfiability of the model, or generating only optimal systems based on objective functions. only optimal systems based on objective functions based on one or more QAs. This thesis aims to find a native modelling and reasoning approach for a unified Quality and Variability Model (QVM). Variability and Quality Model (QVM). The aim is to develop an approach that supports modelling and reasoning for the reasoning oriented optimisation of numerical characteristics, an algebraic framework for unified QVMs, an online eco-assistant for optimising a user-constrained solution space measured for quality, and an algorithm and an online quality, and an algorithm and a web tool for learning the influences of energy and characteristics of user-constrained, domain-unknown and partially measured solution spaces.</p>
Replication Package: Product-Line Engineering for Smart Manufacturing: A Systematic Mapping Study on Security Concepts
<p><strong>Welcome to the public repository for the additional content of the paper "Product-Line Engineering for Smart Manufacturing: A Systematic Mapping Study on Security Concepts", accepted at the ICSOFT 2024.</strong></p> <p>This repository provides additional information to the conducted mapping study, including the following file:</p> <ul> <li>analysis_sheet_ICSOFT2024.csv: sheet containing information regarding the analysis results of 43 included papers based on the extraction criteria.</li> </ul>
AutoML Applied to Time Series Analysis Tasks in Production Engineering
<p>The dataset is accompanying the paper "AutoML Applied to Time Series Analysis Tasks in Production<br>Engineering" (<a href="https://doi.org/10.1016/j.procs.2024.01.085" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2024.01.085</a>). It contains the experimental data referred to in the paper as "KIOptiPack".</p>
Technological supply product qualities engineering
<p>The monograph comprehensively outlines the most important aspects and<br> provisions regarding heredity in the processing of parts and<br> assembly of components of mechanical engineering products that affect their operation<br> characteristics. The physical and mechanical properties of the structural elements are presented<br> inherited materials, their geometric parameters that are formed during<br> technological processes. Methods of product quality management are offered<br> machine-building enterprises at the stages of design and production.</p>
Productivity simulation framework in software engineering - Bibliometric data
<p>Bibliographic data from the Web of Science and SCOPUS relate to this search string: <em>framework AND simulation AND productivity AND (software development OR software engineering)</em>. The authors also include the Bibliometrix application report.</p>
Open data for publication: Advanced catalyst for CO2 photo-reduction: From controllable product selectivity by architecture engineering to improving charge transfer using stabilized Au clusters
<p>Original data for publication: Advanced catalyst for CO2 photo-reduction: From controllable product selectivity by architecture engineering to improving charge transfer using stabilized Au clusters, published in Small, 2023.</p> <p>The dataset is organized according to the Figures in the manuscript.</p>
Biosensor-driven strain engineering reveals key cellular processes for maximizing isoprenol production in <em>Pseudomonas putida</em>
Open the record for dataset details and reuse information.
NMR-Guided Rational Engineering of Endocellulase from Acidothermus Cellulolyticus for Reducing Product Inhibition
<p>These are the plumed input files needed to reproduce the funnel metadynamics results for cellobiose binding to WT 1ECE, Y245G mutant, and W212A mutant. </p>
Engineering and Production of the Light-Driven Proton Pump Bacteriorhodopsin in 2D Crystals for Basic Research and Applied Technologies
<p>Data to Stauffer et al. (2020), Methods Protoc.</p>
Supplementary Material for "Engineering of a β-galactosidase from Bacillus coagulans to relieve product inhibition and improve hydrolysis performance""
<p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Tab. S1<a href="https://zenodo.org/record/5109535">:</a> Primers of alanine scanning</p> <p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Tab. S2<a href="https://zenodo.org/record/5109535">:</a> Primers of N148 saturation mutation</p> <p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Fig. S1<a href="https://zenodo.org/record/5109535">:</a> Reaction mechanism of β-galactosidase.</p> <p> </p>
Data from: Genome engineering allows selective conversions of terephthalaldehyde to multiple valorized products in bacterial cells
<p>Deconstruction of polyethylene terephthalate (PET) plastic waste generates opportunities for valorization to alternative products. We recently designed an enzymatic cascade that could produce terephthalaldehyde (TPAL) from terephthalic acid. Here, we showed that the addition of TPAL to growing cultures of<em> Escherichia coli</em> wild-type strain MG1655 and an engineered strain for reduced aromatic aldehyde rection (RARE) strain resulted in substantial reduction. We then investigated if we could mitigate this reduction using multiplex automatable genome engineering (MAGE) to create an <em>E. coli </em>strain with 10 additional knockouts in RARE. Encouragingly, we found this newly engineered strain enabled a 2.5-fold higher retention of TPAL over RARE after 24h. We applied this new strain for the production of <em>para</em>-xylylenediamine (pXYL) and observed a 6.8-fold increase in pXYL titer compared to RARE. Overall, our study demonstrates the potential of TPAL as a versatile intermediate in microbial biosynthesis of chemicals that derived from waste PET.</p>
Data from: Genome engineering allows selective conversions of terephthalaldehyde to multiple valorized products in bacterial cells
Open the record for dataset details and reuse information.
Multiplex secretome engineering enhances recombinant protein production and purity
GEO Series GSE144624. Cricetulus griseus. 18 samples. Type: Expression profiling by high throughput sequencing.
Biosynthesis of the high-value natural products bottromycin and pamamycin from lignin-, plastic- and seaweed-based monomers using engineered Streptomyces lividans
GEO Series GSE246798. Streptomyces lividans. 9 samples. Type: Expression profiling by high throughput sequencing.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.