dataesr/scientific-paragraphs-categorization huggingface dataset:
Visualization: 3D rendering and interaction with numerical and categorical data The projection operator generates a 3D texture which can be directly rendered using Direct Volume Rendering methods, as described by  Stegmaier et al. (2005). To support the study of the structure, i. e. , of the evolution of the cross-section selection over time, compared to additional information present in the dataset, we annotate the information through color mapping. Due to the nature of our datasets, we consider an opaque rendering avoiding semitransparency, in order to limit color distortion when using color to encode information. We encode numerical or categorical information in textures, used as a 2-entry array, according to time and object identifier. As time and identifier are directly accessible in the 3D volume, the information to display on the visualization can be color mapped according to each object, and switched at low computational cost.
• In case of moving objects, slightly oblique cutting can help track the object over time. This type of cut was used to generate the cut in Figure  4. Selection operator: This tool is a pointer that displays summarized information of the hovered object, such as its identifier. This is a detail-on-demand operator that can display additional information on the object on click. It appears as a red arrow object, so that the user can put the pointer precisely on the desired object, providing a highlight feedback upon hovering or selecting. Switching the color mapped information: When various numerical or categorical information are present in the dataset, the user can scroll through the list of information displayable (cf Figure  3 ). As detailed in Section 3. 3, the underlying operation corresponds to switching the texture containing the information, and can thus be executed interactively.
This feature helps the user to track the objects in time, or to find objects of interest in a cluttered environment. The user, by selecting objects using the selection operator described in Section 3. 4. 1, can change the state of the object-From normal to highlighted to masked-Upon clicking the trigger of the controller. The state is also propagated over time, in order to highlight all the instances of the given object over time. Furthermore, if the object follows a tree hierarchy in time, such as the cells with their children cells in our example dataset, the operation is also propagated to the children objects as well. Yet, it should be noted that to achieve such propagation, the dataset requires identifiable objects over time and hierarchy information. Figure  3  shows an example of object tracking.
Use case: Application to cell division and morphogenesis analysis In this section, we demonstrate the potential of the STH applied to the visualization and analysis of spatio-temporal data from the recordings of embryonic developments of a Phallusia mammillata, a marine invertebrate. We present the studied dataset, which has been already shown in the previous section, and detail a VR application in which the STH has been integrated. Finally, we describe three use cases, based on recommendations for classic analytical tasks by the domain experts we worked with, illustrating the potential benefits of the STH.
Embryonic development dataset The data set used to illustrate the STH data is a live recording of the embryonic development of the Phallusia mammillata, a marine invertebrate animal of the ascidian class. The embryo was imaged every 2 minutes for 6 hours using confocal multiview light-sheet microscopy, generating a 4D dataset with isotropic spatial resolution of several terabytes  (Guignard et al. , 2017). The data was then segmented using the ASTEC pipeline (Adaptive and Tracking of Embryonic Cells) designed by  Guignard et al. (2017) , and meshed using the VTK library  (Schroeder et al. , 2004)  and MeshLab  (Cignoni et al. , 2008) , producing a surface-based spatiotemporal dataset of a few hundred megabytes representing the embryo. Examples of the surface meshed model of some of the 180 time points recorded are shown in Figure  1.
In addition, the ASTEC pipeline extracted global lineage trees of the embryo, i. e. , the tracing of cellular genealogy derived from cell divisions and migration. Other categorical or continuous data, such as the volume of cells or the remaining lifespan-i. e. , time before the next division-Were computed or added by the community of experts working on the dataset. We also had access to the ANISEED  (Brozovic et al. , 2017)  database, providing us with categorical information about the expression of various genes in the cells.
VR visualization application Taking advantage of the large workspace offered by immersive environments, we developed a VR application for the user to interact with the meshed model, in addition to the STC visualization. We based our environment on the framework MorphoNet, an online interactive browser for the exploration of morphological data, by  Leggio et al. (2019). The development of the application was done using Unity 3D and the HTC Vive was the main visualization and interaction system. Our framework displays the dataset described above using meshed model of the embryo at each time point, as well as a STC based on a cross-section placed close to the median plan of the embryo, as shown in Figure  5. The color mapped on the visualizations here corresponds to the volume of the cells. Regarding the user interface, a virtual desk contains all the available tools that the user could grab using the trigger button of the HTC Vive controller.
Expert feedback analysis During the design and development of our method, five domain experts helped us by providing advice to formalize the use cases presented before to test the method, as well as the priorities of biologists in terms of tool to approach such use cases, and by testing the application. In addition to informal discussions during the design of the system, the domain experts tested the application in two different sessions, at different stages of the development of the prototype. They all participated to both sessions, which were 3 months apart, for 1 hour for each expert and session. The domain experts had no previous experience with Virtual Reality, three of them had experience with the MorphoNet framework and the dataset. The two others had no experience with either. The first session consisted in a presentation of an early version of the visualization method, that did not include most interactions of filtering and selection.
In other remarks, the STC was deemed "similar to a cell lineage tree  (Sulston et al. , 1983)  but with spatial and especially neighbourhood information"; The latter giving a supplementary dimension in the analysis of the data. This, aided with adequate color mapping, could be relevant in cases of analysis of signals or communications between cells for example. Few other improvements were suggested during these tests, most of them regarding the addition of further information in the environment, or enhancing some controls. The need of comparing and linking different datasets was also especially pointed out, echoing with  Kim et al. (2017)  observations.
General discussion While the evaluations described in the paper have showed the potential usages and advantages of the STH for the visualization of 3D spatio-temporal morphogenesis data, there is yet a number of additional future works in order to cope with its current limitations. First, the generated STC visualizations are based on a projection operator which enables the visualization of a subset of the original 4D data. Although this approach generates a compact representation of the spatio-temporal data, it also results with a loss of spatial information and can be sensible to strong motions within the dataset. For example, strong motions can be particularly problematic for objects close to the cutting plane that can result in wrong interpretations (e. g. , an object shrinking when it is just moving away from the clipping plane).
In the current implementation of the system, we tried to compensate for these negative effects by the juxtaposition of the meshed model, which gave additional contextual information missing in the STC visualizations. Nevertheless, future works should explore how to adapt the projection operation to extract more reliable information. For example, the Frontiers in Bioinformatics frontiersin. org 10 plane could be adjusted over time to track an object of interest or consider the internal motions of the objects, potentially extending the cutting plane to an arbitrary surface. A second aspect that should be further studied, is the usage of the STH for other spatio-temporal datasets. In order to complement the examples shown in this paper, we provide additional generated STCs from two additional datasets.
The first dataset shown in Figure  7 , left side, is a simulation in 42 time points of an abstract oryzalin-treated organ. The appearing outgrowth is obtained by locally softening the membrane of a shoot-apical meristem filled with uniform and steady turgor pressure. The stress magnitude on each cell, notably implied by this outgrowth, is colormapped on the STCs. The second dataset, shown in Figure  7 , right side, is part of a 3D temporal imaging atlas of cell morphology for the C. elegans embryo. The recording includes 150 time points, from the 4 to 350 cells stages. The STCs displayed show the remaining lifespan of each cell as a colormap1. However, the examples and use cases described in this paper are related to the analysis of morphogenesis. In these datasets, the temporal and spatial coherency was high, i.
e. , motions between two consecutive data points were relatively low, with quite a low spatial density, and the different structures visualized are well-defined (i. e. , cells). The STC visualizations had a number of cavities which allowed a good tracking of the cells and were easily explored using the additional cutting operations. It remains unknown whether the STH approach would be still usable for spatio-temporal datasets with lower temporal and spatial coherency, and higher spatial density. In such situations, the STC visualization could be denser and less continuous, potentially impacting its comprehension. Nevertheless, the usage of the STH will still be dependent of the purpose of the analyst. A third aspect that should be also noted is the exploration of other direct volume rendering methods.
Indeed, a wide range of methods existing for the enhancement of DVR rendering methods  (Jönsson et al. , 2014) , particularly with the objective of improving the comprehension of the complex and interacted structures that volumetric datasets have  (Preim et al. , 2016). In the presented work, we leveraged stereoscopic viewing for improve the understanding of STC rendering, but other use cases might require the highlight of certain structures  (Bruckner and Gröller, 2007)  or to consider other shading methods  (Díaz et al. , 2017). Further work could explore the role of additional rendering methods, and in particular the use of transfer functions with different levels of opacity of the understanding and interpretation of the generated visualizations. Finally, a recurrent comment from the domain experts was the addition of annotation functionalities to the system.
Conclusion In this paper, we have proposed a novel spatio-temporal visualization based on the Space-Time Cube visualization. The proposed visualization, the Space-Time Hypercube, extends the STC visualization to consider a third spatial dimension in the data. To enable a direct visualization, we proposed a projection operator on based on a user-driven cross-section defined in 3D space. The projection of the hypercube, consequently a STC, contains only a partial spatial information of the dataset, but creates a view containing temporal information. Numerical and categorical information could be displayed as well on the visualization. We juxtaposed and linked the and original dataset visualizations in a VR application, taking advantage of immersive environments benefits in terms of visualization and interaction in 3D.
Various tools for exploration, filtering or tracking objects apply transformations on both visualization and come to assist in the analysis of the dataset. Moreover, we illustrated the potential usages of the STC in the context of morphogenesis. The evaluation with domain experts showed that the STC visualization presents a number of benefits with respect to traditional visualizations, especially for the detection of events with a temporal relevance. The STH approach could pave the way to new types of visualization and interaction methods for 3D spatio-temporal data, and we believe that such tools will help the adoption of VR technologies for data visualization.
However, orientation averaging significantly increased the computation time. Therefore, computations were restricted to 27 target orientations ( = 0°, 120°, 240°; Θ = 0°, 60°, 120°; and Φ = 0°, 120°, 240°) due to the limita- tions in computational resources and the enormous time required for light scattering calculations. The graphical representations of the calculated Mueller matrix elements are shown in Supplementary Fig. 1. The results are also compared with Mie calculations for a solid sphere of radius 140 nm and refractive index 1. 48, obtained by using the code TUMiescat. c [46]. Remarkably, significant variations in the scattering properties were observed for all the three target geometries as compared to that of the solid sphere, which may be attributed to their structural (surface roughness and presence of spikes in virus geometries) and compositional (refractive indices for virus body and nucleic acid) differences.
Results and discussion The Mueller matrices of the SARS-CoV-2 models with 15, 20, and 40 spikes were illuminated with light of 0°, 45°, and 90°; subsequently, RCP polarization and output polarization states were determined. The simulation was performed using light of two different wavelengths corresponding to 200 nm and 350 nm. Using MATLAB Software, Stokes vector parameters, S 0 , S 1 , S 2 , and S 3 were reconstructed for both input and output states. The output Stokes vectors and polarization parameters at 0°, 45°, and 90° scattering angles, calculated for these three SARS-CoV-2 models, for various input polarization states are shown in Table  2. For these scattering angles, all the three target geometries were found to exhibit greater values of Stokes polarization parameters (DOP, DOLP, and DOCP) at an incident wavelength of 350 nm than that of 200 nm.
Conclusion During the past two years, humankind has witnessed unprecedented threat from SARS-CoV-2 that caused millions of deaths and adversely modulated lives and livelihoods throughout the world. The spike proteins of SARS-CoV-2 is the key of the virus that enables it to bind and invade human cells, and the virus infectivity increases significantly with a larger number of spike proteins. In this work, we have carried out light scattering calculations on SARS-CoV-2 models with 15, 20, and 40 numbers of spike proteins on the viral capsid surface to investigate how these numbers affect the light scattering properties by using DDSCAT 7. 3. 0 software package based on discrete dipole approximation. Notably, significant variations in the scattering properties were observed for all the three target geometries compared to that of a solid sphere of equal size, suggesting that the number of spikes is an essential parameter to understand the interaction of light with such virus particles.
Funding Open access funding provided by  Manipal Academy of Higher Education, Manipal. The work is funded by the  Global Innovation and Technology Alliance  (GITA),  Department of Science and Technology (DST)  (Project Number -GITA/DST/TWN/P-95/2021 ),  Indian Council of Medical Research (ICMR)  (Project Number -ITR/Ad-hoc/43/2020-21 , ID No. 2020-3286 ),  University Grants Commission (UGC)  (Grant No. F. 5-376/2014-15/MRP/ NERO/2181 ),  Assam Science Technology and Environment Council  (Grant No. :  ASTEC/S&T/1614/8/2018-19/1159 ), and  Science and Engineering Research Board  (SERB),  Department of Science and Technology (DST)  (Grant No. CRG/2019/004868 ),  Government of India, India.
Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties -known to have different responses to drought.
A group led from China also sequenced a reference Indica variety (IR-93), and independently annotated gene models  [3]. Despite Indica rice varieties accounting for around six times the size of international market as Japonica rice varieties  [4] , the Nipponbare assembly is generally considered the "canonical reference" genome for research and breeding efforts. There are two current, non-synchronised annotations of the Oryza sativa Japonica (Nipponbare variety) genome assembly: the Rice Genome Annotation Project at Michigan State University (MSU)  [5]  and the Rice Annotation Project Database (RAP-DB)  [6]. MSU gene models are no longer updated but still used frequently in research projects and cited in publications. RAP-DB is regularly updated, and serves as the source for gene models loaded into other databases such as Ensembl Plants and Gramene  [7, 8]  (the two databases being mostly synchronised and using the same underlying technologies), and the source protein sequences for UniProtKB (UniProt Knowledge-base)  [9] , the most popular protein knowledge-base.
Over several years UniProtKB has performed some manual curation, where improvements can be identified in protein sequences, meaning that UniProtKB protein sequences are not identical to Ensembl Plants/Gramene. Other key initiatives and datasets include the rice 3,000 genomes project  [10] , which provides a resource for understanding genetic variants within Oryza sativa. More recently, new rice "platinum standard" genomes are being sequenced sequenced  [11, 12] , with new predicted gene models for these varieties now available in Ensembl Plants and Gramene. Genetic variation data and GWAS analyses can be key for identifying candidate genes or chromosomal regions associated with traits of interest. However, discovery of a SNP (Single Nucleotide Polymorphism) significantly associated with a trait can give only limited information about associated biological function or mechanism.
In this work, we aim to provide a high-quality resource providing phosphorylation sites in rice. Phosphosites on proteins are detected and localised on a large scale using tandem mass spectrometry (MS), via "phosphoproteomics" methods. These methods generally involve the proteins extracted from samples being digested by enzymes such as trypsin and phosphorylated peptides being enriched in these samples using reagents such as TiO2, or other metal ions, attached to a column (affinity chromatography), to which phosphate binds preferentially. These bound peptides are then eluted and analysed using liquid chromatography-mass spectrometry (LC-MS/MS)  [15]. The tandem MS data is then usually queried against a protein sequence database, via a search algorithm. Scores or statistics are calculated for the confidence that the correct peptide sequence has been identified (including the mass of any PTMs), and then for PTM-enriched data, a second step is usually performed to assess the confidence that the site of modification has been correctly identified, if there are multiple alternative potential residues in the peptide.
We have recently published an approach to assess the global false localization rate (FLR) of PTMs using searches for PTMs on decoy amino acids, and demonstrated its importance for controlling multiple sources of error in the analytical pipeline  [16]. We have also extended the model to demonstrate how to combine evidence coming from multiple spectra, and to combine evidence and control FLR across multiple studies  [17]. Many papers that report phospho-proteomes do not adequately control for site FDR, and just use ad hoc score thresholds for peptide identification or site localisation scores. For example, in the popular PhosphoSitePlus resource we estimated that around ~67% of the phosphosites reported in the database are likely to be false positives, and those with only an observation from one single study are very unlikely to be true  [18].
To provide FDR-controlled data on phosphosites to the research community requires reprocessing MS data, using well controlled statistical procedures, and applying post hoc approaches to control FDR when aggregating data across multiple studies. There are several online databases for gaining information about PTMs in plants, sourced from published studies. The Plant PTM Viewer  [19]  aggregates results from published studies that used PTM enrichment and MS, and has good coverage of studies for a range of PTM types, including phosphorylation, acetylation, ubiquitination and several others. Over 13,000 rice proteins are reported to be modified, and >27,000 Arabidopsis thaliana proteins, mapped to ~15,000 genes (translated from 54,000 transcripts of the 27,600 coding genes). For detailed study of the A.
thaliana phosphoproteome, there also exists the PhosPhAT database  [20] , which similarly loads phosphoproteomics data from published studies on Arabidopsis, containing evidence for 55,000 phosphorylation sites on ~9,000 A. thaliana proteins. Plant PTM Viewer and PhosPhAT are useful for community resources, although by loading data from published studies (rather than reprocessing data), are likely to contain variable data quality and cannot control for FLR across multiple datasets. UniProtKB is a leading cross-species resource for studying protein function, including extensive expert manual curation. For PTM-related data, UniProtKB mostly loads data by curating individual studies, and has not previously loaded large-scale MS data reporting on plant PTMs. PTMs are reported on just 320 rice proteins in the UniProtKB and on 2,763 Arabidopsis proteins (October 2023, Release 2023_04).
The PRIDE database at the European Bioinformatics Institute (EMBL-EBI) is the largest MS-based proteomics data repository  [21]. PRIDE is leading the ProteomeXchange (PX) consortium of proteomics resources, whose mission is to standardise open data practices in proteomics worldwide  [22]. PeptideAtlas is also a PX member, focused on the consistent reanalysis of datasets  [23]  for a variety of species, including recent builds for Arabidopsis  [24]. Widespread public deposition of proteomics data in PX resource now enables meta-analysis studies to be performed, by reanalysing groups of related datasets. As part of the "PTMeXchange" project, our consortium aims to complete a large-scale re-analysis of public PTM enriched datasets, using robust analysis pipelines incorporating strict FDR control, and correction for FDR inflation in meta-analyses.