Japan Recon Acc (RA): Stock: Oth Changes in Assets Acc(OA): Non Fin Assets data was reported at 0.000 JPY bn in 2014. This stayed constant from the previous number of 0.000 JPY bn for 2013. Japan Recon Acc (RA): Stock: Oth Changes in Assets Acc(OA): Non Fin Assets data is updated yearly, averaging 0.000 JPY bn from Dec 1994 (Median) to 2014, with 21 observations. The data reached an all-time high of 0.000 JPY bn in 2014 and a record low of -9,144.200 JPY bn in 2011. Japan Recon Acc (RA): Stock: Oth Changes in Assets Acc(OA): Non Fin Assets data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Japan – Table JP.A081: SNA 93: Benchmark Year=2005: Integrated Accounts: Reconciliation Account: Annual. Changed from SNA 1993 to SNA 2008 Replacement series ID: 383696257

Proteins used in conformation-dependent sequence tolerance benchmark.

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NOAA Great Lakes Environmental Research Laboratory collected the data from moored Realtime Coastal Observation Network, ReCON, Muskegon M45 Buoy, Lake Michigan, an in-situ moored station, in the Great Lakes. Observations have been collected at this location since 2016, this record contains the 2020 observations. Note, the short deployment of this buoy in 2020 is due to COVID-19 and a reduced field work season. The ReCON buoy provides continuous, real-time observations facilitates modification of sampling parameters in anticipation of episodic events, facilitates collection of field samples in response to episodic events, supports long term research, and contributes to sensor and system development. Parameters collected include currents and water temperature. The block of text at the beginning of each file contains information about the location and sensor used to collect data and the data headers followed by the observed data. Column 1 of the data is the timestamp, column 2 is the observed data, and column 3, where applicable, the QARTOD flag. Five QARTOD tests were run including gross range, climatological, spike, rate of change, and flat line tests. The highest value from the five tests were included under the “Qartod†column. If data were known to be invalid, that line of data was removed from the dataset.

Thiele2013 - Stomach lower glandular cells The model of stomach lower glandular cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000 ). This model is described in the article: A community-driven global reconstruction of human metabolism. Thiele I, et al . Nature Biotechnology Abstract: Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus metabolic reconstruction, which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/. This model is hosted on BioModels Database and identified by: MODEL1310110046 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Thiele2013 - Lung pneumocytes The model of lung pneumocytes metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000 ). This model is described in the article: A community-driven global reconstruction of human metabolism. Thiele I, et al . Nature Biotechnology Abstract: Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus metabolic reconstruction, which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/. This model is hosted on BioModels Database and identified by: MODEL1310110010 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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