dataesr/scientific-paragraphs-categorization huggingface dataset:
Following this discussion, Andreas Dräger presented the Systems Biology Simulation Core Library  [84]. He stressed the recent addition of support for SED-ML in this software tool and highlighted some issues related to performing simulations based on SBML models as well as the ability of the software to be expanded to support further model encoding standards (e. g. , CellML, NeuroML). The session finished with a discussion on other potential features that might be desirable in SED-ML. The purpose of SED-ML was clarified, as a medium for exchanging descriptions of simulation experiments between software tools rather than as a definition of the data struc-tures able to encode all the capabilities of any given software tool. With a large portion of the SED-ML community present at the COMBINE meeting, progress was made turning some of these ideas into feature requests and incorporating them in a future version of the SED-ML specification.
Model repositories and meta-data Day four of the meeting focused on model reusability, model management and metadata. Ron Henkel (University of Rostock, Germany) introduced a novel approach for storing models encoded in SBML and CellML and using graph databases  [88]. Contrary to existing solutions, his database maps the network structure of models and integrates model-related data such as annotations and simulation descriptions. Ron Henkel also demonstrated how he was able to import all of the path2models data  [89]  in his database and search it. Another important aspect of model reuse is provenance. Related to this topic, Martin Scharm (University of Rostock, Germany) talked about current issues with version control in model repositories. He introduced an improved method to detect differences in versions of a model  [90].
His software tool BudHat  [91]  lets users compare two versions of an SBML or CellML encoded model, and creates histories for each distinct model. Daniel Arend (IPK Gatersleben, Germany) introduced the e!Dal Data Repository  [92, 93]  as a framework for sharing, versioning and reusing existing data. In particular, he stressed the goal of long-term preservation of data managed inside the e!Dal system, and the importance of metadata when doing so. Dagmar Waltemath (University of Rostock, Germany) concluded the first session with a discussion about a common annotation scheme for all COMBINE standards. Her intention was to homogenize annotations in SBML, CellML, NeuroML, SED-ML (and others) to make these annotated data more comparable on a semantic level. Tommy Yu (University of Auckland, New Zealand) started the second session with an update on recent developments in the Physiome Model Repository, PMR2  [8, 94].
APPARATUS Stimuli were displayed on a Mitsubishi Diamond pro 2070 1024 × 768 px CRT monitor with a 100 Hz refresh rate. Subjects viewed the stimuli from a distance of 40 cm, through a set of mirrors, such that the left eye saw the left half of the screen, and the right eye saw the right half of the screen. The experiment was written and executed using Matlab and Psychophysics toolbox version 3. 1  (Brainard, 1997; Pelli, 1997; Kleiner et al. , 2007). Statistical analysis was performed using Matlab and R (R Foundation for Statistical Computing Vienna, Austria).
STIMULI The set of famous faces comprised 31 females and 30 males, all famous actors or politicians within the United States (for names, see Supplementary Table  1 ). The set of unfamiliar faces comprised 10 females and 10 males; they were, in fact, pictures of Israeli celebrities that were chosen to ensure rough equivalence in attractiveness and image quality with the famous faces. All face images used in the experiment were processed to remove most low level differences: they were converted to gray scale then normalized using a combination of in-house Matlab code and functions from the SHINE toolbox  (Willenbockel et al. , 2010  and Figure  1 ). Raw face images were 400 × 400 px in size. Our normalization procedure included the following steps: image transformation to match face sizes and positions based on manually annotated eye and mouth points (using Procrustes analysis, i.
ACKNOWLEDGMENTS This research, and  Julien Dubois , were supported by the  G. Harold and Leila Y. Mathers Charitable Foundation ,  Nathan Faivre  by the  Fyssen Foundation ,  Gregory Izatt  by a  Summer Undergraduate Research Fellowship  from the  California Institute of Technology. The authors are very grateful to  Hagar Gelbard-Sagiv  for providing some of the face images used in our experiments.
It is, however, clear that the model of pure substitutional sites wildly overestimates the effective carrier concentration in AZO. The core level spectra, analyzed using the XPSpeak software, 12 provide further insight. The Zn 2p 3/2 , Zn 3s, and Zn 3p core levels in the intrinsic ZnO can be deconvoluted into three components, shown in Fig. 4. All peaks have a 90% Gaussian/10% Lorentzian shape. The FWHM for a given core level is constant: 1. 34, 2. 25, and 2. 35 eV for the 2p, 3s, and 3p core levels, respectively. The main component at a binding energy of 1022. 69, 139. 95, and 88. 91 eV for the 2p, 3s, and 3p levels is due to the ZnO matrix. The low binding energy (LBE) component has already been shown to be due to Zn reduction caused by incident radiation, as observed on the Zn 3p core levels in ZnO and AZO.
ENDscript 2 is a friendly Web server for extracting and rendering a comprehensive analysis of primary to quaternary protein structure information in an automated way. This major upgrade has been fully reengineered to enhance speed, accuracy and usability with interactive 3D visualization. It takes advantage of the new version 3 of ESPript, our well-known sequence alignment renderer, improved to handle a large number of data with reduced computation time. From a single PDB entry or file, ENDscript produces high quality figures displaying multiple sequence alignment of proteins homologous to the query, colored according to residue conservation. Furthermore, the experimental secondary structure elements and a detailed set of relevant biophysical and structural data are depicted. All this information and more are now mapped on interactive 3D PyMOL representations.
INTRODUCTION Sequence similarity search and multiple sequence alignment (MSA) are methods of choice for solving or interpreting bioinformatics and biological problems  (1). They can address many questions and thus are the basis of numerous evolutionary and comparative studies, e. g. homology identification, protein function, structure and interaction predictions, computer-aided mutagenesis, phylogenetic analyses, etc. Over the years, the exponential growth of sequence and structure databases content  (2)  has raised several challenging issues concerning, e. g. data curation, storage, search, accessibility and visualization. The Web server ENDscript 1  (3, 4)  was created in 2002 to facilitate the generation of figures containing a large amount of protein sequences and secondary structure information.
Since then, similar programs have been released with extended functionalities (e. g. STRAP  (5) , Aline (6), Jalview 2  (7)  or PROMALS3D  (8) ). ENDscript is derived from our well-known ESPript program that renders sequence similarities and secondary structure elements from aligned sequences with numerous options to optimize and enhance their depiction. ESPript version 1 (9) and 2 (4) belong to a family of programs developed for non-interactive MSAs representation (e. g. Alscript  (10) , BoxShade or PRA-LINE  (11) ). To date, several biotool Web servers are interfaced with ESPript: connections are available from T-Coffee  (12) , NPS@ (13), MultAlin  (14)  (each performing sequence analyses and similarity searches) and from the protein domain database ProDom  (15). Here, we present ENDscript 2, a friendly Web server for extracting and rendering a comprehensive analysis of primary to quaternary protein structure information in an automated way.
The new ENDscript 2 server (http://endscript. ibcp. fr) is a major upgrade of ENDscript 1. x, which has been entirely re-engineered to be faster and to process information from thousand of sequences and structures thanks to a parallel programming. It can now generate, with a few mouse clicks and without queuing, high quality figures with the new version 3 of ESPript (http://espript. ibcp. fr) as well as interactive 3D representations with a novel automated PyMOL script generator.
The experimental secondary structure elements of each identified homologous protein are depicted at the top of the sequence block if their 3D structures are known. The third and fourth illustrations consist in two interactive 3D representations of the PDB query. To take advantage of these latter, the program PyMOL (The PyMOL Molecular Graphics System, Schr ödinger LLC, http://www. pymol. org) has to be installed on the user's computer. The first PyMOL representation is named 'Cartoon': this is a ribbon depiction of the PDB query colored as a function of similarity scores calculated from the preceding MSA. The color ramping from white (low score) to red (identity) allows to quickly locate areas of weak and strong sequence conservation on the query structure. The second PyMOL representation is titled 'Sausage': it shows a variable tube depiction of the C␣ trace of the query (see an example in Figure  1C ).
For this representation, all homologous protein structures were superimposed on the PDB query and the radius of the tube is proportional to the mean rms deviation per residue between C␣ pairs. The same white to red color ramping is used to visualize possible substitutions in sequence. Hence, the user can identify areas of weak and strong structural conservation and correlate this result with sequence conservation. For these two PyMOL representations, a solventaccessible surface mapped with the same coloring code can be switched on or off via the PyMOL control panel (see an example in Figure  1D ). If applicable, the user can also display an assortment of supplementary information compiled by ENDscript: biological assembly and multiple NMR models; disulfide bridges; nucleic acids, ligands or monatomic elements and their contacting residues; strictly conserved residues; PDB SITES markers.
All these features are editable thanks to the PyMOL graphical user interface, and publication-quality pictures can rapidly be obtained with its built-in ray-tracing function. Depending on his skill in PyMOL usage, the user has the choice to download an all-in-one and ready-to-use Py-MOL. pse session file, or a. zip archive file containing a Py-MOL. pml script and associated required files to manually edit them to his need. Therefore, the user has full flexibility to customize these representations automatically produced by ENDscript. In addition, an MSA file with secondary structure elements in Stockholm format is generated by ENDscript and can be examined (and modified) online with the JalviewLite viewer  (7). Finally, hypertext links to the PDB record of each identified protein of known structure similar to the query are presented.
Changes and new features in ESPript program and Web server The ENDscript Web server uses the core Fortran program ESPript in its backend. The new version 3 of ESPript has been deeply modified to fulfill two key requirements driven by ENDscript 2: minimizing its execution time and handling a large number of data. For this purpose, OpenMP parallelization directives have been added to the PostScript rendering core routines of ES-Pript in order to take advantage of multicore and multiprocessor architectures. Hence, the resulting MSA PostScript files are no more rendered line-by-line but in parallel by using as many cores/processors the machine has. As a result, the execution time bottleneck constituted by the rendering process has been drastically reduced, this permitting the rapid depiction without queuing of up to 2500 aligned sequences decorated with their secondary structure elements on 4500 columns.
In addition, ESPript 3 now runs on an x86 64 platform, allowing the program to address memory in a more efficient way and to handle very large tables. The program was compiled with gfortran, part of the GNU Compiler Collection, with the -mcmodel = medium flag to allocate tables exceeding 2GB. This choice was essential as the data that ESPript is led to manage is growing proportionally to the number of sequences and structures in databases implemented in ENDscript. The ESPript graphical interface has been considerably revamped in order to better meet the needs of the users who are now guided through the whole process by tooltips, detailed help topics and a new tutorial accessible at any time. New coloring schemes and markers have been implemented as well as output and paper size formats: ESPript renders publication-quality illustrations in most common file formats (PostScript, PDF, PNG, TIFF) and sizes (US letter, A4, A3, A0 and the 'Tapestry' format--0.
New features and enhancements in ENDscript Web server Even if the general process scheme remains unchanged between version 1 and 2 of ENDscript, we considerably reengineered the initial code to enhance speed, accuracy and usability. In this goal, the new ESPript 3 program, described above, was of primary importance. In addition, helper programs, part of the ENDscript pipeline, were chosen for their efficiency and their ability to use multicore machines. Hence, we replaced the programs BLAST and ClustalW2 by their latest revisions (BLAST+  (17)  and Clustal Omega  (18) , respectively) to gain in scalability, accuracy and performance. In the same goal, two MSA programs were added to the ENDscript pipeline, namely MAFFT  (19)  and MSAProbs  (20). In the previous version of ENDscript, only two sequence databases were available (UniProtKB/Swiss-Prot and PDBAA, the sequence database derived from the PDB).
In ENDscript 2, we added 12 complete genome databases, the UniProtKB/TrEMBL as well as the PDBAA95, PDBAA90, PDBAA70 and PDBAA50 containing the results of the clustering of protein chains in the PDB at 95%, 90%, 70% and 50% sequence identity, respectively (see Supplementary Table  S1 ). As for the ESPript Web server, the ENDscript graphical user interface was utterly remodeled for improved usability with tooltips, detailed help topics and tutorial. The results, separated in hierarchical sections, are now presented in a clearer manner. Finally, we opted for the molecular visual-ization program PyMOL as default viewer for the interactive 3D representations as it is multi-platform and widely adopted by biologists and structural biologists. ENDscript takes full advantage of the convenient PyMOL control panel, notably of its ability to show and hide information or objects with a single click, this facilitating the analysis of the results.
ENDscript is open to external bioinformatics services In addition to the above-mentioned enhancements and new features, we designed ENDscript 2 as an open platform for the visualization of multiple biochemical and structural information. Indeed, ENDscript has the ability, for its primary to quaternary structure representations, to depict a large range of supplementary data coming from external sources. Hence, any biotool Web server calculating or predicting structure-related properties can use ENDscript for an effective display. This implies that ENDscript is supplied with a modified PDB file conforming to some simple annotation conventions and modifications. In practice, the property to be displayed by ENDscript must be numerically expressed per residue or per atom in order to replace the B-factor or occupancy values.
A REMARK record in the PDB file header must specify a keyword associated to the interfaced service as well as the minimal and maximal values of the property--this allowing ENDscript to normalize the data. In concrete terms, colored bars or special characters in the flat representations can present this supplementary information. It can also be displayed in 3D with PyMOL by highlighting the appropriate residues or atoms with specific coloring scheme and/or by any other means (spheres, dots, meshes, surfaces, etc. ). A proof of concept of this new ENDscript feature is presented in Supplementary Data 1. Biotool Web server administrators interested in interfacing their service with ENDscript can contact the authors to obtain the annotation rules and the connection protocol.
CASE STUDY Catalases are tetrameric heminic enzymes that decompose hydrogen peroxide into water and oxygen. They serve to protect cells from the toxic effects of hydrogen peroxide. As a case study, we used ENDscript to decipher features in the crystal structure of Proteus mirabilis catalase (PDB entry 2CAH)  (21). The two fundamental residues of the heme-iron catalytic site are a distal histidine and a proximal tyrosine. A unique methionine sulfone is observed in the distal site of P. mirabilis catalase. Another peculiarity of this bacterial catalase is its ability to bind nicotinamide adenine dinucleotide phosphate (NADPH) for the prevention of inactivation by hydrogen peroxide  (22). The first flat figure clearly shows that the catalase structure has an ␣+␤ topology (Figure  1A  and Supplementary Data 2).
By contrast the N-terminal region, which protrudes out of the protein core, is surprisingly well conserved. In fact, this region is deeply buried in the biological tetramer, this being visible by displaying the biological assembly (Figure  1D  and Supplementary File 1) automatically incorporated by ENDscript in the PyMOL session file. Finally, thanks to a preset button on its control panel, PyMOL can display the protein solvent accessible surface colored according to the level of sequence conservation (Figure  1D ).
CONCLUSION ENDscript 2 is a major update of our joint ESPript/ENDscript Web service, which has benefited over the past decade of a mean of 1500 unique visitors a month from more than 25 countries submitting over 14 000 jobs monthly. It takes advantage of the new version 3 of ESPript, which previous releases total more than 2000 combined cross-citations in 'Web of Science' and are supported by the SBGrid Consortium (Harvard Medical School, http://www. sbgrid. org). The new ENDscript Web server has been conceived to be fast and convenient. Thanks to its automated pipeline and a parallel programming, ENDscript can deliver most results within 1 min. No particular knowledge in bioinformatics is needed to obtain comprehensive and relevant illustrations. However, demanding or expert users can modify settings to fine-tune ENDscript to their needs.
ACKNOWLEDGMENTS We would like to thank  Dr Christophe Guillon  for extensive beta-testing and careful proofreading of this manuscript and  Dr Magali Dejob  for her advices on the development of the graphical user interface. We acknowledge the  Computer Resource Center  ( IBCP FR3302 ), namely  Alexis Michon  and  Dr Christophe Blanchet  for providing us such robust facilities. Finally, we are grateful to the  W324 Nucleic Acids Research, 2014, Vol. 42, Web Server issue ESPript/ENDscript 's users for their comments, suggestions and bug reports.
44) × 1 + f 2 (A 2 )κ(λ 2 (A 2 )) q 2 (A 2 ) 2 τ 2 2 (A 2 ) ñ2 ñ2 + L 4 A e 6A 2 V f (λ 2 (A 2 ), τ 2 (A 2 )) 2 κ(λ 2 (A 2 )) 2. This function is returned in the code by APrimeFromSols. It is the fully scaled form, but expressed as a function of the coordinate A 2 , which has not been shifted, i. e. it is in the same coordinate system as all the other functions returned by the code. It is level 2 in the same sense as the rest of the level 2 functions: the coordinate system is such that the horizon is at zero, but the units are such that it needs no further factors of Λ scale. It can be used fully consistently with all the other output functions, but note that if for some reason the coordinate system would be shifted again, Φ would then be scaled again according to (B. 34). ). An interesting point is that the dependence on the actual numerical solution is precisely the same as for the entropy density s in (B.
26). Thus one has a physical interpretation for the input parameter ñ, it is simply ñ = 4πn(λ h ; ñ)/s(λ h ; ñ), where one also inserted the constants given in (4. 17 for which we need to integrate (B. 37). The correct boundary condition is that Φ( A h ) = 0, yielding µ = ∞ A h Φ (A)dA = ∞ 0 Φ 2 (A 2 )dA 2 (B. 47) This, and also the function Φ(A 2 ), is returned in the code by AAndMuFromSols, with ∞ replaced by the upper limit A max of the range for which the equations have been solved. In addition, the code uses L A = 1, but any other choice can be implemented by simply scaling n and µ. C Determination of τ h (λ h ; m q ) The quark mass m q can be computed from the formulas presented in Appendix B given the initial conditions at horizon. However, for computing physical results, we For µ the smallest values of ñ are 0.
Acknowledgments We thank  Blaise Goutéraux ,  Misha Stephanov  and  Aleksi Vuorinen  for discussions. This work was partially supported by  European Union 's  Seventh Framework Programme  under grant agreements ( FP7-REGPOT-2012-2013-1 ) No  316165 ,  PIF-GA-2011-300984 , the  ERC Advanced  Grant  BSMOXFORD 228169 , the  EU program Thales   MIS 375734  and was also co-financed by the  European Union (European Social Fund, ESF)  and  Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF)  under "Funding of proposals that have received a positive evaluation in the 3rd and 4th  Call of ERC  Grant Schemes". TA thanks the  Vaisala foundation  for financial support. KT acknowledges financial support from the  Academy of Finland  project  267842.
To be able to directly compare the staining of nsl1 WT (wild-type) and mutant larvae, the chromosomal squashes were prepared on the same slide, and images of wild-type and mutant polytene chromosomes were taken in the same tile scan. The male sample was distinguished from the female sample using MSL1 as an X-chromosomal marker (Supplemental Fig. S7C ). Consistent with the reduction of MBD-R2 in ChIP analyses, we observed a striking reduction of MBD-R2 staining on the mutant chromosomes in comparison with wild type in male and female larvae (Fig. 4D ; Supplemental Fig. S7C ). These data clearly show that the NSL1-WDS interaction is essential for the viability of Drosophila and the proper targeting of the NSL complex to the promoters of target genes in vivo.
Substitutions in the lower-affinity WDS-binding motif of NSL2 seem to have no effect on WDS levels, consistent with the major role of NSL1 in WDS recruitment. We show that the NSL1-WDS interface mutagenesis triggered a decrease of NSL1 binding to promoters of the NSL target genes, resulting in fly lethality. In addition, ChIP and polytene chromosome immunostaining revealed a similar reduction of the MBD-R2 subunit on mutant chromosomes compared with wild type. Interestingly, while the binding of the FlagTnsl1 WT transgene was also. The NSL1-WDS interaction is required for proper targeting of NSL1 to the promoters of target genes. (A) NSL1 ChIP from whole male larvae. qPCR was performed using primers corresponding to the promoter (P) and end (E) regions of genes. The list of target and nontarget genes was chosen based on the genome-wide data  (Raja et al.
Figure4. The NSL1-WDS interaction is required for proper targeting of NSL1 to the promoters of target genes. (A) NSL1 ChIP from whole male larvae. qPCR was performed using primers corresponding to the promoter (P) and end (E) regions of genes. The list of target and nontarget genes was chosen based on the genome-wide data (Raja et al. 2010; Lam et al. 2012). ChIP recovery was calculated over the input DNA (shown as percentage [%]). The end of target genes and both the promoter and the end of nontarget genes were used as negative controls. The error bars represent standard deviations of three biological replicates. (B) As in A, but this time Histone H3 ChIP from whole male larvae. This provides a control for the quality of the chromatin preparations. (C) As in A, but this time MBD-R2 ChIP from whole male larvae.