These data are described in Dennis EJ et al 2023 published in Bio-Protocol. Briefly, this is a tiff image stack of sagittal slices of an average brain of multiple Rattus norvegicus rats and serves as a common coordinate framework for rat researchers. mPRA is only male brains, defined by external genitalia (testes, penis). fPRA uses the same definition, but a lack of testes or penis.

3D moment invariants are important tools for 3D image feature representation. In this paper, we introduced a novel approach for constructing 3D moment invariants using Gaussian geometric moments. Our proposed method demonstrated invariance under translation, rotation, and scale transformations. The numerical experiments validate the invariance and robustness of the proposed method, comparing it with traditional 3D geometric moments and revealing superior performance in the presence of noise and transformations. Additionally, the method is applied to content-based 3D image retrieval, exhibiting promising results through Minkowski distance-based retrieval on the Princeton Shape Benchmark (PSB) database.

Simulation input files for the parsec 2.1 benchmark suite. These files are no longer available on the Princeton University website.

Main datasets used, type, spatial resolution and time period.

The size of the problem at different input scale for workload ep.

GO slim data for the Grech gene list, retrieved from the GO Term Mapper (https://go.princeton.edu/cgi-bin/GOTermMapper)

System configurations of two Sandy Bridge servers.

Benchmark suites of representative workloads.

A static mirror of the files downloadable at https://interacdome.princeton.edu/.I am not the author of this dataset. I am hosting this public resource for the purpose of creating a static (unchanging) link from which the files can be permanently accessed with. If you use this dataset, cite the authors and study:Kobren, S.N. and Singh, M. (2018) "Systematic domain-based aggregation of protein structures highlights DNA-, RNA-, and other ligand-binding positions." Nucleic Acids Res, 47(2): 582–593. doi: 10.1093/nar/gky1224.InteracDome Web Server

Simulations illustrating the results of full-FORCE.Thanks to Eli Pollock (epollock@mit.edu) for the Python implementation.Contact Brian DePasquale (depasquale@princeton.edu) for questions about the MATLAB implementation.A more frequently maintained repository can be found here: http://www.princeton.edu/~briandd/.

This repository contains two main packages that were developed as a part of:"Deconstructing Gastrulation at Single-Cell Resolution" by Tomer Stern, Stanislav Y. Shvartsman, and Eric F. Wieschaus, Princeton University, 2021.--------------Package #1: Segmentation and tracking code and demo data.To use it - download the file, unzip it, and follow the instructions on the "Instructions.docx" file.--------------Package #2: Data analysis (includes code and data for plotting the analyses presented in the manuscript).It contains whole embryo cell segmentation and tracking of the two embryos used in the referenced publications, as well as several extracted features, such as cell areas and intercalation events.It also contains code assisting in loading the data, visualizing it, and calculating a variety of additional morphological attributes.To use it, download the file, unzip all into a single directory, open the "DG_main_script" script in matlab, and follow the instructions at the top comment.--------------For any questions / comments / assistance in setting the code up or using it, please feel free to contact me at:tstern@princeton.eduor:stern.tomer@gmail.comHappy gastrulation!

Three-Hundred Random Asian Faces. LAST UPDATE: November 2018.DongWon Oh (New York University)Shuo Wang (West Virginia University)Alexander Todorov (Princeton University).These 300 images are "twins" of 300 Caucasian faces that were randomly generated using the Facegen Modeller program (http://facegen.com) Version 3.1. The exact procedures are described in Oosterhof and Todorov 2008 (visit for details: http://tlab.princeton.edu/databases/randomfaces/). In the "300 Random Asian Faces", the FaceGen parameter coordinates of the 300 random Caucasian FaceGen faces are shifted so that the coordinates of the face images center around the average coordinates of the East Asian face in the FaceGen model, which were calculated from the actaual East Asian faces, measured via 3d laser scanning. This shifting procedure essentially makes the faces on average appear more East Asian.This face image set can be used for example when building a data-driven face evaluation model of Asian faces (e.g., a face model of trustworthiness judgement). See Oosterhof & Todorov (2008) and Todorov & Oosterhof (2011) for details.If you use any of the images from the set, cite the following article:Oosterhof, N. N., & Todorov, A. (2008). The functional basis of face evaluation. Proceedings of the National Academy of Sciences of the USA, 105(32), 11087–11092. http://doi.org/10.1073/pnas.0805664105

This dataset has been superseded by a newer version:Chenoweth, Katie, Rebecca Sutton Koeser, Alexander Baron-Raiffe, Renée Altergott, Chad Córdova, Austin Hancock, Chloé Vettier, Jean Bauer, Benjamin Hicks, Nick Budak, and Kevin McElwee. 2021. Derrida's Margins Datasets. Version 1.1. October 2021. Distributed by DataSpace, Princeton University. https://doi.org/10.6084/10.34770/2ezk-1104.OverviewDerrida’s Margins is a website and online research tool for annotations from the Library of Jacques Derrida, housed at Princeton University Library (PUL). Jacques Derrida is one of the major figures of twentieth-century thought, and his library--which bears the traces of decades of close reading--represents a major intellectual archive. The first phase of the project focused on annotations related to Derrida’s landmark 1967 work De la grammatologie (Of Grammatology).Data collection methodsWorks cited by Derrida in De la grammatologie were documented in a private Zotero library using a custom tagging system to indicate the location and kind of references in a particular work. That data was imported by script into a custom database, creating records for books, sections of books, and journal articles. Records were also created for references in De la grammatologie based on information encoded in the Zotero tags. The book and reference data was further cleaned and refined in the database after import; items with digital editions available from PUL were linked via IIIF. Interventions were documented by project researchers using a custom-built annotation solution, linked to digitized page images from PUL digital editions for this collection. The current phase of the project only includes structured data for annotation interventions and not insertions.Data dictionaryURIs are used as unique identifiers for references, books, and annotations across all datasets, to allow linking the information. URIs will resolve to the best available representation of that content on the Derrida’s Margins website (in some cases, this is a search result).Intervention data fieldsid: unique URI for each interventionbook id: unique URI for the item where the intervention occursbook title: display title for the item where the intervention occurspage: label for the page in the book where the intervention occurstags: list of tags describing the intervention. Tags currently include:underliningcirclingarrowbracket(s)linecorrectionmarginal markpunctuation markflyleaf notetext illegibletranscription uncertainblue inkblack inkred inkpenciltext content: content of the annotation, for verbal annotationstext language: language of the annotation, for verbal annotationstext language code: ISO language code for the language of the annotationquote content: a transcription of the annotated passagequote language: the language of the annotated passagequote language code: ISO language code for the annotated passageannotator: authorized name of the annotator, if known

This WORDNET TENSOR DATA consists of a collection of triplets (synset, relation_type, triplet) extracted from WordNet 3.0 (http://wordnet.princeton.edu). This data set can be seen as a 3-mode tensor depicting ternary relationships between synsets.The definitions file (wordnet-mlj12-definitions.txt) contains one synset per line with the following format: synset_id (a 8-digit unique identifier) intelligible name (word+POS_tag+sense_index), definition. The previous 3 pieces of information are separated by a tab ('\t').All wordnet-mlj12-*.txt files contain one triplet per line, with 2 synset_ids and relation type identifier in a tab separated format. The first element is the synset_id of the left hand side of the relation triple, the third one is the synset_id of the right hand side and the second element is the name of the type of relations between them.There are 40,943 synsets and 18 relation types among them. The training set contains 141,442 triplets, the validation set 5,000 and the test set 5,000.All triplets are unique and we made sure that all synsets appearing in the validation or test sets were occurring in the training set.The WN18.zip file contains the other files, with more compression than the default "download all".

This dataset has been superseded by a newer version:Chenoweth, Katie, Rebecca Sutton Koeser, Alexander Baron-Raiffe, Renée Altergott, Chad Córdova, Austin Hancock, Chloé Vettier, Jean Bauer, Benjamin Hicks, Nick Budak, and Kevin McElwee. 2021. Derrida's Margins Datasets. Version 1.1. October 2021. Distributed by DataSpace, Princeton University. https://doi.org/10.6084/10.34770/2ezk-1104.OverviewDerrida’s Margins is a website and online research tool for annotations from the Library of Jacques Derrida, housed at Princeton University Library (PUL). Jacques Derrida is one of the major figures of twentieth-century thought, and his library--which bears the traces of decades of close reading--represents a major intellectual archive. The first phase of the project focused on annotations related to Derrida’s landmark 1967 work De la grammatologie (Of Grammatology).Data collection methodsWorks cited by Derrida in De la grammatologie were documented in a private Zotero library using a custom tagging system to indicate the location and kind of references in a particular work. That data was imported by script into a custom database, creating records for books, sections of books, and journal articles. Records were also created for references in De la grammatologie based on information encoded in the Zotero tags. The book and reference data was further cleaned and refined in the database after import; items with digital editions available from PUL were linked via IIIF. Interventions were documented by project researchers using a custom-built annotation solution, linked to digitized page images from PUL digital editions for this collection. The current phase of the project only includes structured data for annotation interventions and not insertions.Data dictionaryURIs are used as unique identifiers for references, books, and annotations across all datasets, to allow linking the information. URIs will resolve to the best available representation of that content on the Derrida’s Margins website (in some cases, this is a search result).Datasets generated by export from a public Zotero library generated from the Derrida's Margins project database.

Additional file 4: The GO Term Finder results of the Type I-Type IV genes. The significant GO terms (top 10 hits) shared among each group of Type I-Type IV genes from S. cerevisiae were found by using GOTERMFINDER ( http://go.princeton.edu/cgi-bin/GOTermFinder ). Only top 10 hits in each type of genes were shown in the table. (XLS 26 KB)

These files represent the full dataset and the R code to reproduce the Figure and Supplementary Figure from the article "Ammonium sensitivity of biological nitrogen fixation in sulfate-reducing diazotrophs and coastal salt marsh sediments", by Romain Darnajoux, Linta Reji, Xin Rei Zhang, Katja E. Luxem, and Xinning Zhang (Princeton University, Department of Geosciences).