Independent Projects

supplementary information: figures and tables

New Optical Coherence Tomography Biomarkers Identified with Deep Learning for Risk Stratification of Patients with Age-related Macular Degeneration

This project collects and maintains metadata templates designed and used at the UMass Chan BioImage DMS Core and built in collaboration with the CBI Open Science Project. The templates are based on the REMBI recommendations and on the NBO-Q Microscopy Metadata specifications. These templates contribute to FAIR bioimaging data in North America, and are meant to be utilized to support image data annotation in the OMERO database.

FUNCEMM is a project bringing together 2 teams from France and Austria focusing on synthetic methylotrophy.

The BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to facilitate seamless human-machine interaction while creating, verifying, evaluating, curating, and expanding executable models of intra- and intercellular signaling. This format allows a human user to easily preview and modify any model component, while it is at the same time readable by machines and can be processed by a suite ...

SDBV group using Hub

Based on the combination of sensor and big data revolutions, PHENET (HE INFRA-TECH) will equip crop and ecosystems RI with innovative services based on tools and methods developed in the frame of the project and allowing enhanced capacity to future-proofing agroecosystems. These services will be excellent tools for users addressing environmental and societal challenges such as climate change adaptation / mitigation and agroecology transition.

Testing out FAIRDOM-Seek

MESI-Review 2024

Cell biological and proteogenomic study of the chloroplast of the marine, bloom-forming dinoflagellate P. cordatum

This data contains fish data such as fish abundance, fish community structure data, fish species data obtained in the study, fish productivity and also fish length-weight relationships.

This research discusses what is the status of fisheries provisioning services in Jatigede Reservoir and what anthropogenic pressures in the form of community activities affect the status of fisheries provisioning services.

MESI-STRAT Review

Current chemical concept recognition tools have demonstrated significantly lower performance for in full-text articles than in abstracts. Improving automated full-text chemical concept recognition can substantially accelerate manual indexing and curation and advance downstream NLP tasks such as relevant article retrieval. Participating in BioCreative Track NLM-Chem we focus identifying chemicals in full-text articles (i.e. named entity recognition and normalization).

This investigation serves as supplementary material for a SWAT4HCLS publication that describes minimum metadata and provenance requirements for reproducible enrichment analysis results.

Functional enrichment analysis is an essential downstream process in high throughput omics studies, such as transcriptomics and proteomics. By using the Gene Ontology (GO) and its annotations (GOA), underlying functional patterns of over-representation can be identified, leading to ...

Aims: The immune response is important for mediating the benefit of cardiac cell therapies. The role of varied immune responses in influencing the outcome of cardiomyocyte cell transplantation after myocardial infarction was investigated. Methods and Results: Cardiac flow cytometric analysis of C57BL/6J and T- and B cell deficient Rag2del mice revealed varied CD11b, natural killer and dendritic cell responses following sham injection and a disparate macrophage response after myocardial infarction. ...

Members of the genus Aromatoleum are cosmopolitan in diverse habitats and utilize a broad range of recalcitrant organic molecules coupled to denitrification or O2-respiration. To gain a holistic understanding of the model organism A. aromaticum EbN1T, we here studied its catabolic network dynamics in response to 3-(4-hydroxyphenyl)propanoate, phenylalanine, 3-hydroxybenzoate, benzoate and acetate utilized under nitrate-reducing vs. oxic conditions. Multi-OMICS (transcriptome, proteome and metabolome) ...

1. To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
2. To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M. hyopneumoniae for vaccine optimization
3. To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2) aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a serum-free growth medium and; 4) assess, at genome scale, the metabolic ...

Lauren Baugh, Brittany A. Goods, Juan S. Gnecco, Yunbeen Bae, Michael Retchin, Constantine N. Tzouanas, Megan Loring, Keith Isaacson, Alex K. Shalek, Douglas Lauffenburger, Linda Griffith

https://www.medrxiv.org/content/10.1101/2022.01.29.22269829v1

Endometriosis is a debilitating gynecological disorder affecting approximately 10% of the female population. Despite its prevalence, robust methods to classify and treat endometriosis remain elusive. Changes ...

Juan S. Gnecco, Alexander Brown, Kira Buttrey, Clara Ives, Brittany A. Goods, Lauren Baugh, Victor Hernandez-Gordillo, Megan Loring, Keith Isaacson, Linda G. Griffith

https://doi.org/10.1101/2021.09.30.462577

The human endometrium undergoes recurring cycles of growth, differentiation, and breakdown in response to sex hormones. Dysregulation of epithelial-stromal communication during hormone cycles is linked to myriad gynecological disorders for which treatments ...

Chemical named entity recognition (NER) is a significant pre-processing task in natural language processing. Identification and extraction of chemical entities from biomedical literature and entities linking to the knowledge base are essential steps for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we ...

This study describes the results of a survey on enrichment analysis tool usage and provenance reporting for a corpus of SARS-CoV2 data.

This study contains the singele nuclei data analysis part of the Bl6 and Rag2del comparison. Here, we used Seurat, harmony, and monocle for an in-depth analysis.

Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to “low quality” potentially leading to data misinterpretation. Common standard quality control parameters involve the ...

This study contains our snRNA-Seq based comparison of whole hearts from Fzt.DU and Bl6 mice published in Cardiovascular Research.

This study includes the single snRNA-seq in whole adult murine hearts from an inbred (C57BL/6NRj) and an outbred (Fzt:DU) mouse strain in comparison to publicly available scRNA-seq data of the tabula muris project.

This study contains our single nuclei characterisation of whole hearts from Fzt.DU mice published in Cells.

Predictions made using the core model for combinatorial perturbations to the model simulating combined effects from OE, KO mutants, perturbations and time series concentrations.

Internal metabolites concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations External metabolite concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations Mutant (OE, KO, perturbation) metabolite measurements

Training of the core model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data. The core model contains reactions in glycolysis, pyruvate metabolism and ATPase

Validation of the core model of glycolysis, pyruvate metabolism and ATPase reaction using OE, KO mutant samples and perturbation samples

This section contains all the raw data and files required for each figures.

RobOKoD algorithm was, designed then implemented as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain. It was shown to perform better than similar methods (OptKnock, and RobustKnock).

OptKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

RobustKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

Training of the model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data.

Validation by simulating independent OE, KO mutant and perturbation samples, using sampling of the gausian distribution based on the mean and SD of measurements per sample. A 1000 samples of the gausian distribution of the mean and SD was performed per sample to show error in the measurements and how it propegates in predicted metabolite concentration in SS

Comparison of Kcat values from the model and values from literature.

Protein copy number at 6h, 12h, 24h, 48h, 72h, 96h, average values and SD for the measurements

Metabolomics time series measurements for internal metabolites for 6h, 24h and 48h for multiple experiments. Largely based on MAss spectrometry, bioluminescence kits to measure NAD, NADH at 24h, other time points are infered from relative measurements times the absolute measurements at 24h.

Simulation of OE mutants targetting enzymes in the model, combined with metabolite concentrations and enzyme fold change of from the 40 samples. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.

Measurements of external metabolites based on growth curve data. Flux estimates for uptake of external metabolites such as glucose and production rates for external metabolites lactate and acetate

Construction and manual curated Genome Scale Metabolitic model of M. hyopneumoniae. Dynamic flux balance analysis was performed for glucose uptake

Contains the analysis of the internal metabolite concentrations of the 40 independend samples Pearson correlation was used to generate heatmaps Pearson correlation with p-value cutof of 0.001 was used and as input for a correlation network (grouping using H-clust) Principal component analysis was performed on samples, F-ion and H-ion data combined and seperately Zip files contains the data (FC.txt), PCA and heatmap plots and the script to re-generate these plots

Metabolic control analysis: Local control coefficients for 40 independent samples based on 100x sampling from the measurement distribution Global control analysis based on 100.000 Latin Hypercube sampling from the parameter search range (0.01-100 for Km values and 0.001-1000 for Vmax values)

The associated zip files contains all input files and a Jupyter notebook to rerun sampled simmulations, combined simmulations, parameter scan for the model with addition of an oxygin inhibiton of LDH, local- and global-sensitivity analysis and plot simmulation output in various formats. In addition the zip file contains the py36.yaml file that can be used to recreate the model simmulation environment using Anaconda making all simmulations completely reproducable. All information on how to use ...

Synergist or antagonist interactions in mixed cultures of Candida species, according to HWP1, ALS3 and SAP1 gene expression levels.

Candida yeast quantification from 20-h old cultures and posterior adjustment to 107 viable cells/mL using a hemocytometer.

Standard curve of HWP1, ALS3 and SAP1 genes examined by CT values and log cDNA dilutions.

Melting curves of HWP1, ALS3 and SAP1 genes of C. albicans, C. parapsilosis and C. tropicalis indicated in peaks.

Amplification curves of HWP1, ALS3 and SAP1 genes of C. albicans, C. parapsilosis and C. tropicalis.

Raw data of Figure 5, main text

Raw data of Figure 4, main text

Raw data of Figure 3, main text

raw data of Figure 2

This data contains fish data such as fish abundance, fish community structure data, fish species data obtained in the study, fish productivity and also fish length-weight relationships.

This data showed all water parameters and the calculation of water quality status using STORET methods in Jatigede Reservoir

This data showed all water parameters and the calculation of water quality status using STORET methods in Jatigede Reservoir

Batch sample publishing

Batch sample publishing

Batch sample publishing

Batch sample publishing

Batch sample publishing

Batch sample publishing

Batch sample publishing

Batch sample publishing

The FEM models how metabolic slowdown will induce the age-related changes of weight gain, insulin resistance, basal inflammation, mitochondrial dysfunction, as well as the age-related disease of atherosclerosis, via a series of unavoidable homeostatic shifts.

Underlying R script for the investigation of immune cells. Script contains basic data processing, as well as a DE and monocle analysis.

Stoichiometric model in SBML format using the acetate-aerobic standard scenario.

Please note that SBML was exported using the sbmlwriter class of Metano. This file was not used for the actual analyses.

This stoichiometric model of Aromatoleum aromaticum EbN1 is a genome-scale model and comprises 655 enzyme-catalyzed reactions and 731 distinct metabolites.

The model is in the plain-text reaction format of Metano that is human-readable and can be opened with every text editor. To run this version of the model, please use the Metano Modeling Toolbox (mmtb.brenda-enzymes.org) and the associated scenario files.

A population of turtles have between 1 and 3 genes contributing to the strength of selective destruction, which can either cause ageing or allow for negligible senescence.

Model of selective destruction in a single population of cells with differing sensitivities for growth. Fast growing cells can be epigenetically converted to slower cells rather than simple cell death as in previous models.

Model of unselective destruction in a single population of cells with differing sensitivities for growth

Model of selective destruction in a single population of cells with differing sensitivities for growth

Here, we describe the index file generation of the mm10 genome, the genome alignment with kallisto, and quantification with bustools to obtain the used spliced / unspliced transcript input.

Here is the detailed R script to generate the input needed by scSynO for synthetic cell generation and classification model training.

The code that can be embedded into any other Seurat data processing workflow is:

cell_expression_target_cluster <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = "target_cluster_number")]) cell_expression_all_other_clusters <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = ...

Single nuclei transcriptomics data as .csv files from the Allen Brain atlas data set of mus musculus (https://celltypes.brain-map.org/) have been utilized as an input for scSynO. The underlying analysis is part of the manuscript entitled "Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling". Data anaylsis and visalizations were mainly generated with the Seurat R package (https://satijalab.org/seurat/archive/v3.2/spatial_vignette.html)

Dynamic model of glycolysis, pyruvate metabolism and NoxE. The model is parameterized by selecting the best out of 100 parameter set using Copasi's Genetic algorithm with 1000 itterations and 500 simmulatanious models.

The new GEM of S. coelicolor developed by Tjasa Kumelj, Snorre Sulheim, Alexander Wentzel and Eivind Almaas in 2017/2018

Core model with the addition of a NoxE reaction to regenerate NAD using O2. COPASI’s build in Evolutionary programming algorithm was used to estimate parameters using a maximum of 2000 generations with a population size of 100 models with value scaling as weights to train the 5 parameters of the NoxE reaction.

Butanol producing iNS142, redesigned using RobOKoD.

E.coli Core model, with additional reactions added to generate the beta-oxadation cycle. This is the basic model used in RobOKoD: microbial strain design for (over)production of target compounds (http://fairdomhub.org/publications/236).

Detailed description of the methods applied for proteomic analyses of P. cordatum heat stress response

Detailed description of the methods applied for metabolomic analyses of P. cordatum heat stress response