cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100267
title: Supporting data for "Estimating the total number of phosphoproteins and phosphorylation sites in eukaryotic proteomes."

description: Phosphorylation is the most frequent post-translational modification made to proteins and may regulate protein activity as either a molecular digital switch or a rheostat. Despite the cornucopia of high throughput phosphoproteomic data in the last
decade, it remains unclear how many proteins are phosphorylated and how many phosphorylation sites (p-sites) can exist in total within a eukaryotic proteome. We present the first reliable estimates of the total number of phosphoproteins and phosphorylation sites (p-sites), for four eukaryotes (human, mouse, Arabidopsis, and yeast).<br>
In all, 188 high-throughput phosphoproteomic datasets were filtered, compiled and studied along with two low-throughput compendia. Estimates of the number of phosphoproteins and p-sites were inferred by two methods: Capture-Recapture, and fitting the saturation curve of cumulative redundant vs. cumulative non-redundant phosphoproteins/p-sites. Estimates were also adjusted for different levels of noise within the individual datasets and other confounding factors. We estimate that in total, 13,000, 11,000 and 3,000 phosphoproteins and 230,000, 156,000 and 40,000 p-sites exist in human, mouse and yeast, respectively, whereas estimates for Arabidopsis
were not as reliable.
Most of the phosphoproteins have been discovered for human, mouse and yeast, while the dataset for Arabidopsis is still far from complete. The datasets for p-sites are not as close to saturation as those for phosphoproteins, Integration of the low-throughput data suggests that current high-throughput phosphoproteomics is capable of capturing 70-95% of total phosphoproteins, but only 40-60% of total p-sites.
DOI: 10.5524/100268
title: Supporting data for "An improved assembly of the loblolly pine mega-genome using long-read single-molecule sequencing"

description: The 22 gigabase genome of loblolly pine (Pinus taeda) is one of the largest ever sequenced. The draft assembly published in 2014 was built entirely from short Illumina reads, with lengths ranging from 100 to 250 base pairs (bp). The assembly was quite fragmented, containing over 11 million contigs whose weighted average (N50) size was 8,206 bp. To improve this result, we generated approximately 12-fold coverage in long reads using the Single Molecule Real Time (SMRT) sequencing technology developed at Pacific Biosciences. We assembled the long and short reads together using the MaSuRCA mega-reads assembly algorithm, which produced a substantially better assembly, P. taeda version 2.0. The new assembly has an N50 contig size of 25,361, more than three times as large as achieved in the original assembly, and an N50 scaffold size of 107,821, 61% larger than the previous assembly.
DOI: 10.5524/100269
title: Supporting data for "The use of Oxford Nanopore native barcoding for complete genome assembly"

description: The Oxford Nanopore Technologies MinION(TM) is a mobile DNA sequencer that can produce long read sequences with a short turn-around time. Here we report the first demonstration of single contig genome assembly using Oxford Nanopore native barcoding when applied to a multiplexed library of 12 samples and combined with existing Illumina short-read data. This paves the way for
the closure of multiple bacterial genomes from a single MinION(TM) sequencing run, given the availability of existing short-read data. The strain we used, MHO_001, represents the important community-acquired methicillin resistant Staphylococcus aureus lineage USA300.
<br>
Using a hybrid assembly of existing short read and barcoded long read sequences from multiplexed data, we completed a genome of the S. aureus USA300 strain MHO_001. The longread data represented only ~5-10% of an average MinION(TM) run (~7x genomic coverage) but, using standard tools, this was sufficient to complete the circular chromosome of S. aureus strain MHO_001 (2.86 Mb) and two complete plasmids (27 Kb and 3 Kb). Minor differences were noted when compared to USA300 reference genome, USA300_FPR3757, including the translocation, loss and gain of mobile genetic elements.
<br>
Here we demonstrate that MinION(TM) reads, multiplexed using native barcoding, can be used in combination with short-read data, to fully complete a bacterial genome. The ability to complete multiple genomes, for which short-read data is already available, from a single MinION(TM) run is set to impact on our understanding of accessory genome content, plasmid diversity and genome rearrangements.
DOI: 10.5524/100281
title: Supporting data for "Genome sequence of pacific abalone (Haliotis discus hannai): the first draft genome in family Haliotidae"

description: Abalones are large marine snails in the family Haliotidae and the genus Haliotis belonging to the class Gastropoda of the phylum Mollusca. The family Haliotidae contains only one genus, Haliotis, and this single genus is known to contain several species of abalone. With 18 additional subspecies, the most comprehensive treatment of Haliotidae considers 56 species valid. Abalone is an economically important fishery and aquaculture animal which is considered a highly-prized seafood delicacy. The total global supply of abalone has increased fivefold since 1970s and farm productions increased explosively from 50 mt to 103,464 mt in the past forty years. Additionally, researchers have recently focused on Abalone given their reported tumor suppression effect. However, despite the valuable features of this marine animal, no genomic information is available for Haliotidae family and related research is still limited. <br>
In order to construct the H.discus hannai genome, a total of 580G base pairs using Illumina and Pacbio platforms were generated with 322-fold coverage based on the 1.8Gb estimated genome size of H.discus hannai using flow cytometry. The final genome assembly consisted of 1.86Gb with 35,450 scaffolds (&gt;2kb). GC content level was 40.51%, and the N50 length of assembled scaffolds was 211kb. We identified 29,449 genes using Evidence Modeler based on the gene information from ab initio prediction, protein homology with known genes and transcriptome evidence of RNA-seq. 
<br>
Here we present the first Haliotidae genome, Haliotis discus hannai, with sequencing data, assembly, and gene annotation information. This will be helpful for resolving the lack of genomic information in the Haliotidae family as well as providing more opportunities for understanding gastropod evolution.
DOI: 10.5524/100301
title: Supporting data for "Draft genome sequence of the Tibetan medicinal herb, Rhodiola crenulata"

description: Rhodiola crenulata, one of the well-known Tibetan medicinal herb, is mainly grown in high-altitude regions of Tibet, Yunnan and Sichuan provinces in China. In the past few years, increasing published studies on pharmacological activities of R. crenulata, have strengthened our understanding into its active ingredient composition, pharmacological activity and mechanism of action. The findings also provided strong evidences supporting the important medicinal and economical values of R. crenulata. Meanwhile, some Rhodiola species are becoming endangered because of overexploitation and environmental destruction. However, little is known about the genetic and genomic information of any Rhodiola species. <br>
Here, we reported the first draft assembly of R. crenulata genome, which was 344.5 Mb (25.7Mb Ns), accounting for 82% of the estimated genome size, with the scaffold N50 length of 144.7 kb and the contig N50 length of 25.4 kb. The R. crenulata genome was not only highly heterozygous but also highly repetitive with ratios of 1.12% and 66.15%, respectively, based on the k-mer analysis. Furthermore, 226.6 Mb transposable elements were detected, of which 77.03% were long terminal repeats. In total, 31,517 protein-coding genes were identified, capturing 86.72% of expected plant genes in BUSCO. Additionally, 79.73% of protein-coding genes were functionally annotated.<br>R. crenulata is an important medicinal plant and also a potentially interesting model species for studying the adaptability of Rhodiola species to extreme environments. The genomic sequences of R. crenulata will be useful for understanding the evolutionary mechanism of stress resistance gene and biosynthesis pathways of the different medicinal ingredients for example, salidroside, in R. crenulata.
DOI: 10.5524/100216
title: Distributed collaboration: the case for the enhancement of Brainspell’s interface

description: The past several decades have seen an explosive growth in the number of published neuroimaging studies. In concert, the demand for freely available and openly accessible study data, that would facilitate future reanalysis, meta-analysis, hypothesis testing and repurposing has also soared. Here we report on developments made to Brainspell one of several web-based initiatives (e.g. BrainMap, NeuroVault, Neurosynth) that allow individuals to search through and organize massive numbers of neuroimaging studies and results in meaningful ways.<br>Distinct from other databases, Brainspell is the first web-based initiative to allow users to manually annotate and curate machine-parsed data, as well as manually extend the database via its crowdsourcing user interface. The goal of our Brainhack project was to improve Brainspells interface. We worked to (a) provide supplementary manual data edit options (b) facilitate efficient manual database extension, and (c) aid meaningful organization of data.<br>We used GitHub to manage the client and server code, and to coordinate its development.
DOI: 10.5524/100220
title: LORIS: DICOM anonymizer

description: The purpose of this Brainhack project was to create a simple application, with the least dependencies, for anonymization of DICOM files directly on a workstation. <br>Anonymization of DICOM datasets is a requirement before an imaging study can be uploaded in a web-based database system, such as LORIS. Currently, a simple and efficient interface for the anonymization of such imaging datasets, which works on all operating systems and is very light in terms of dependencies, is not available. <br>Here, we created a DICOM anonymizer that is a simple graphical tool that uses PyDICOM package to anonymize DICOM datasets easily on any operating system, with no dependencies except for the default Python and NumPy packages. DICOM anonymizer is available for all UNIX systems (including Mac OS) and can be easily installed on Windows computers as well (see PyDICOM installation). The GUI (using tkinter) and the processing pipeline were designed in Python. Executing the anonymizer_gui.py script with a python compiler will start the program. Figure 1 illustrates how to use the program to anonymize a DICOM study. <br>The DICOM anonymizer is a simple standalone graphical tool that facilitates anonymization of DICOM datasets on any operating system. These anonymized studies can be uploaded to a web-based database system, such as LORIS, without compromising the patient or participants identity.
DOI: 10.5524/100221
title: Automatic extraction of academic collaborations in neuroimaging

description: Our ability to quantitatively study large-scale social and behavioural phenomena such as peer influence and confirmation bias within scientific circles rest on quality and relevant data. Yet the compilation of specific coauthorship databases are often restricted to certain well-defined fields of study or publication resources, limiting the extent and depth by which investigations can be performed. Ultimately, we aim to understand how the social construct and its underlying dynamics influence the trajectories of scientific endeavors. This work is motivated by an interest in observing social patterns, monitoring their evolution, and possibly understanding the emergence and spreading of ideas and their biases in the neuroimaging community; central themes to deciphering facts from opinions. However, before being able to fully investigate and address these fundamental and inherently complex questions, we need to address the extraction and validation of data. The goal of this project was to leverage publicly available information on Google Scholar (GS) to automatically extract coauthorship networks. <br>The tool can be accessed through a public website. The site is constructed using a set of openly accessible libraries allowing the display of coauthorship networks as interactive graphs. Visitors can peruse a set of pre-computed networks extracted using custom Python scripts designed to crawl GS based on a set of predefined constraints (e.g. search topic, publication journal). The proposed interface offers seamless manipulation to keep interaction straightforward and easy to use. The simplicity of the design aims to reach a maximum number of users, assuming a minimal level of technical knowledge.
DOI: 10.5524/100222
title: NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files

description: The purpose of developing yet another web-based image viewer, NiftyView, is to use WebGL to take advantage of the parallel computing power in Graphics Processing Units (GPU) hardware for the acceleration of rendering and processing of medical images in web applications. Although several web-based medical image viewers such as Papaya, BrainBrowser and Slice:Drop are currently available, the slow performance of the web-based applications is still one of the major limitations of web-based image viewers. NiftyView is a free web application developed in JavaScript. It has zero footprint; only a web browser and an Internet connection are needed to run NiftyView. Its advantageous over conventional desktop applications in that NiftyView doesnt require installation and constant updates. The current version supports NIfTI and DICOM format. As a minimal image viewer, its a convenient tool for users who need a quick and easy tool for viewing medical images. Currently, the beta version of NiftyView is freely available. <br>NiftyView is developed in JavaScript with jQuery for HTML document manipulation and event handling, jQueryUI for user interface, and DicomParser for parsing DICOM files. Its compatible with popular web browsers including Internet Explorer, Safari, Firefox, and Opera. Either DICOM or NIfTI files can be loaded by dragging files into the browser window. Loaded images can be displayed in single-slice mode or tiled mode. After loading, images are automatically arranged according to the scan IDs for DICOM files and the file name for NIfTI files, respectively. Current functions include image zooming and adjustment of image brightness and contrast. The number of image columns can be adjusted in the tiled mode to maximize the use of the display space. The contrast and brightness of images can be adjusted by clicking and holding the right mouse button or using a double slider widget in the horizontal tool bar at the top of the window. <br>NiftyView is a free and convenient web application for quick and easy viewing of NIfTI and DICOM medical images. We have shown that a factor of six to eight acceleration can be achieved using WebGL for image processing.
DOI: 10.5524/100226
title: Nipype interfaces in CBRAIN

description: We aim at the large-scale, automatic sharing of software tools between neuroimaging processing platforms, which will increase the relevance of such platforms by providing them with richer repositories of higher-quality tools. Currently, efforts are hampered by the repetitive porting of the same few tools in different platforms. During the HBM 2015 Hackathon, we worked on the export of software tools from the Nipype workflow engine to the CBRAIN web platform for distributed computing. Nipype includes a large number of tools that would be useful to CBRAIN users.<br>We developed nipype2boutiques a tool to export Nipype interfaces to the Boutiques tool description format. Boutiques descriptions are importable by CBRAIN and other platforms (Virtual Imaging Platform and the Pegasus workflow engine). They point to a Docker image containing the implementation of the tool. nipype2boutiques relies on nipype_cmd a tool to run Nipype Interfaces as Linux command lines. nipype2boutiques parses the inputs and outputs of a Nipype interface and extracts their name, type, description and position on the nipype_cmd command line. nipype2boutiques then generates a Boutiques descriptor pointing to a Docker image where the Nipype interface is available. Once a Nipype interface is exported using nipye2boutiques it can be imported to CBRAIN.<br>We prototyped a software tool to export Nipype Interfaces as Boutiques descriptors, which can be imported by CBRAIN and other platforms. Although the solution is still limited to simple interfaces, we believe that it has the potential to enable fully automatic tool sharing between Nipype and CBRAIN. Future extensions of nipype2boutiques will be published in the Nipype Github repository.
DOI: 10.5524/100229
title: Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data

description: The laterality index (LI) is one way to assess hemispheric dominance in a variety of tasks, such as language, cognitive functions, and changes in laterality in clinical populations, such as after stroke. In stroke neuroimaging, however, an optimal method of calculating the LI remains controversial, largely due to lesion variability in post-stroke brains.<br>Two main methods of calculating LI have evolved in neuroimaging literature The first, more traditional approach counts the number of active voxels in a given region of interest (ROI) for each hemisphere. This method has been criticized for its inability to account for differences in signal intensity. Hence, a second approach calculates laterality based on the percent signal change within a given region; however, this method also has problems, such as difficulty handling negative values.<br>A laterality toolbox that addresses some of these issues has been implemented in the statistical neuroimaging analysis package SPM, which provides users with options of using either method, along with more advanced statistical tests for robust LI calculations No such toolbox is yet available for FSL. Therefore, we developed a series of scripts to calculate LI in FSL using both voxel count and percent signal change methods. However, in the interest of space, here we present only results from the more robust method of the two (voxel count method).<br>We used fMRI data from two groups of stroke participants who either had right or left hemisphere lesions. Participants observed videos of right or left hand actions, and resulting statistical maps were calculated for each individual. The LI was then calculated per participant, based on the number of active voxels within a given anatomically-defined ROI (the inferior frontal gyrus, pars opercularis). <br>We suggest that stroke neuroimaging might benefit from calculating an average LI across different thresholds (including more lenient thresholds such as z=1.0), in order to provide a more robust outcome that takes into account threshold dependency. This is especially true for individuals with cortical strokes, where the ROI may overlap with the lesion and yield 0 active voxels. This issue of thresholding, specifically for stroke research, is an interesting question that remains to be addressed further. Our scripts for these calculations may be found online at the NPNL resource page.
DOI: 10.5524/100231
title: Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scripts

description: A vast number of clinical disorders may involve changes in brain structure that are correlated with cognitive function and behavior (e.g., depression, schizophrenia, stroke, etc.). Reliably understanding the relationship between specific brain structures and relevant behaviors in worldwide clinical populations could dramatically improve healthcare decisions around the world. For instance, if a reliable relationship between brain structure after stroke and functional motor ability was established, brain imaging could be used to predict prognosis/recovery potential for individual patients. However, high heterogeneity in clinical populations in both individual neuroanatomy and behavioral outcomes make it difficult to develop accurate models of these potentially subtle relationships.<br>Large neuroimaging studies (n&gt;10,000) would provide unprecedented power to successfully relate clinical neuroanatomy changes with behavioral measures. While these sample sizes might be difficult for any one individual to collect, the ENIGMA Center for WorldwideMedicine, Imaging, and Genomics has successfully pioneered meta- and mega-analytic methods to accomplish this task. ENIGMA brings together a global alliance of over 500 international researchers from over 35 countries to pool together neuroimaging data on different disease states in hopes of discovering critical brain-behavior relationships Individual investigators with relevant data run ENIGMA analysis protocols on their own data and send back an output folder containing the analysis results to be combined with data from other sites for a meta-analysis. In this way, large sample sizes can be acquired without the hassle of large-scale data transfers or actual neuroimaging data sharing.<br>A test dataset is available on request; if interested, please email npnl@usc.edu.
DOI: 10.5524/100235
title: Self-organization and brain function

description: Self-organization is a fundamental property of complex systems, describing the order spontaneously arising by the local interactions of the system components not mediated by top-down inputs. Though, self-organizing systems typically possess a large number of components and exhibit complex dynamics, their evolution is deterministic and governed by a small number of order parameters. This property is used here to model the self-organization of the ocular dominance columns of the striate cortex in patterns of neighboring stripes, which respond preferentially to inputs from the left or the right eye. Therefore, the Swift-Hohenberg equation was used which depends on two order parameters. The first one determines the spatial wavelength of the stripes and the second one the branchiness of the pattern. This simple model suffices to study the basic properties of ocular dominance self-organization. Possibly, a combination with models for self-organization in neighboring cortical layers would allow investigating higher organizational principles of the cortex, e.g. the coordination between ocular dominance, orientation, and cytochrome oxidase.