Studies

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.

Construction of a Genome scale constrained-based metabolic modeling of M. hyopneumonia

Proteomics Average and SD data for time series data, 6h, 12h, 24h, 48h,72, 96h per protein

Contains copy number per locus tag at different times of Growth between 0.25h and 96 hours. M. pneumoniae was grown in Batch, cells attached to the bottom of the flask (single cell layer), non stirred, non aerated.