dataesr/scientific-paragraphs-categorization huggingface dataset:
Thus this set of deposited pdb structures display light induced conformational changes that are consistent across many studies and are replicated by independent research groups using different crystal forms. We therefore take the view that these conformational changes most likely represent what is happening in reality. This conclusion comes with the caveat that any motion within 3D crystals is constrained by the need to maintain sufficient crystalline order for diffraction to be recorded. An SVD analysis of this set of structures reveals that the major light induced conformational changes common to these eleven studies correspond to a movement of the extracellular portion of helix C towards helix G, and a movement of the cytoplasmic portions of helix F away from helices A, Fig. 4. Single value decomposition analysis of the major branches (containing two or more pdb entries) of the hierarchal tree shown in Fig.
Difference Fourier analysis of light induced structural changes In the analyses above we sorted the bR-wild type structures (Fig. 2 ) and structural changes (Fig. 3 ) in order to identify similarities and differences in the positions of C α -atoms within all relevant pdb entries. Whereas this analysis extracts conserved global motions, it does not specifically describe local changes in the vicinity of the isomerized retinal. The appropriate method with which to observe local structural changes is difference Fourier analysis, whereby the following Fourier transform (FT) is made to recover the difference electron density: Δρ x ð Þ ¼ FT F exc obs -F gnd obs Á exp iΦ gnd which simply presents the experimental changes in the X-ray diffraction data in real space using the resting state structural model for phases (Φ gnd )  [80].
The critical point is that the resulting difference electron density, Δρ(x), has no phase bias towards the intermediate state model since that model never enters the calculation. Difference Fourier analysis is not always possible since it requires that the two data sets are isomorphous and for highly twinned data it is not possible to extract F obs without additional assumptions. Of the 19 crystallographic studies of light driven structural changes in bR (Table  2 ), crystallographic observations for eight of these are available in the protein data bank. From these data we have calculated Bayesian error weighted difference Fourier electron density maps  [81]  and these are presented in Fig. 5. Three crystal structures of the bR K-intermediate have been described  [16, 57, 64]  and all trapped this early intermediate using green light illumination at 100 K or 110 K (Table  2 ).
9 Å 2 ) relative to the resting state (B = 24. 5 Å 2 ) and this increase was not observed for the SB nitrogen nor Oδ1 and Oδ2 of Asp85. An increase in crystallographic B-factor implies that light-activation also induced some disordering of Wat402 in Lanyi's K-state study. Five studies of the L-intermediate have been reported  [18, 62, 66, 69, 70] , which highlights the high functional importance placed on understanding this structural intermediate which sets the stage for the primary proton transfer event from the SB to Asp85 (Fig. 1 ). Crystallographic data were released for four of these studies  [18, 62, 69, 70]  and error weighted difference Fourier maps calculated from these data are presented in Fig. 5B-E. The L-state of Kouyama  [70]  also shows a negative density peak on Wat402 (visible to 5.
3; 4C, 1O0A ). These authors later repeated this trapping protocol but modified it to collect both resting and illuminated state diffraction data from the same crystal  [66]. Crystallographic data for the latter study were released and are of very high quality, producing the most convincing error weighted difference Fourier electron density map (2NTW-2NTU, Fig. 5C ) of any study of illuminated crystals. A very strong negative difference density feature shows the disordering of Wat402 (visible to 19. 0 σ). Movements of the Lys216 side-chain and backbone; the disordering of Wat400 and Wat401 and a corresponding ordering of Wat451 between Asp85 and Asp212; the breakage of the H-bond interaction from Thr89 to Asp85; the displacement of Trp182 towards the cytoplasm; the beginning of a movement of the sidechain of Arg82 towards the extracellular media; and paired negative and positive difference density features that align along the extracellular portion of helix C, indicating a flex of this helix towards helix G, are all indicated within this difference density map.
For vesicle fusion crystals of bR the photocycle is slowed 100 fold and it was therefore possible to achieve high M-state occupancy when illuminating crystals at room temperature  [71, 72]. Ten pdb entries describe trapped M-states and, with one exception  [65] , all have modeled (to varying degrees) the same structural changes as described above: the disordering of Wat402, Wat400 and Wat401 and ordering of Wat451 between Asp85 and Asp212; the breakage of  ). E, An L-intermediate  [62]  (1VJM-1QHJ). F, An M-intermediate  [72]  (2ZZL-1IW6). G, An M-intermediate (2I20-2I2X)  [68]. H, An O-intermediate  [73]  (3VI0-3VHZ). Both the resting state bR structure (purple) and the corresponding intermediate state structure (Blue, K; red, L; yellow, M; pink, O) are also shown. Difference Fourier map CNS scripts that have been modified to take q-weighting into account were obtained from Thomas Ursby (MAX IV Laboratory, Lund, Sweden) and are provided as supplementary information  [81].
Thus the head-groups of both active site aspartates are cleaved by exposure to X-rays and it cannot be any surprise that the water molecules to which they form H-bonds (Wat400, Wat401 and Wat402) also disorder. At lower X-ray dose another species, termed the orange species since bR changes colour, is also known to build up. Kouyama concluded that the structural changes associated with this species were significantly less than those associated with the K-intermediate, and that the fraction of molecules thus affected could not perform the regular photocycle upon light activation  [57]. Gordeliy and co-workers also carefully investigated the structure of the orange species  [78]  by minimizing the X-ray fluence through a bR crystal (PDB entries 4MD1 (orange species) and 4MD2 (ground state)). The resulting difference Fourier map (4MD1-4MD2, Fig.
3 ; PCC ≤ 0. 32 relative to all other studies). Of the difference Fourier maps calculated from the deposited data, only the L-state study from Lanyi  [69]  shows negative difference electron density extending from Oδ1 to Oδ2 of Asp85 (Fig. 5C ). Even for this case, however, while some radiation damage cannot be ruled out it clearly makes only a minor contribution to the observed difference density. Admittedly, of the three K-state data sets that we deposited fifteen years ago, the other two (data-sets A and B in 1QKP) show indications of radiation damage on Asp85. We are thus again reminded of the benefits of making diffraction data available for posterity since, if the data are available, structural conclusions can be reconsidered in light of new ideas. From these structural observations it appears that a similar mechanism operates in the two cases: when light-activates bR, retinal isomerization breaks the SB-Wat402 H-bond and disorders Wat402.
A unified view of structural changes in the bR photocycle From the analysis presented in Section 5, in which we took a step back and quantitatively analysed global conformational changes of C α atoms in all intermediate trapping and relevant mutation studies of bR, a number of strong conclusions can be drawn: (I) C α movements associated with the low-temperature K-intermediate are small; (II) Reproducible movements of C α atoms (PCC ij ≥ 0. 597) are observed in eleven deposited pairs of pdb entries recovered from studies of light induced structural changes in bR, with the common motions being movements of the extracellular portion of helix C towards helix G, and a movement of the cytoplasmic portion of helix F away from helices A, B and G (Fig. 4F ); (III) The D96G/F171C/F219L bR triple mutant displays a significant structural perturbation corresponding to movements of the cytoplasmic portion of helix F away from helices A, B, C, D, and G (Fig.
These movements grew with a half-rise of 22 μs, preceding the SB deprotonation as measured using transient changes in absorption at 410 nm; these motions increased in amplitude by half again after SB deprotonation with a half-rise of 1. 9 ms; and this conformational change relaxed back to the resting bR conformation with a half-life of 16 ms. Thus experimental data using a completely different, time-dependent X-ray structural probe are in keeping with the major structural conclusions that emerged from our hierarchal sorting of the deposited pdb structures. Our analysis of difference Fourier electron density maps calculated from the deposited crystallographic data also yield remarkably consistent conclusions. Most strikingly, all deposited crystallographic data show a strong negative difference density peak on Wat402, and this is usually one of the strongest features of the difference Fourier electron density map.
5C, G ): this negative peak has a significance of 7. 4 σ in the M-state (2I20-2I1X) and a significance of 19. 0 σ for the L-state (2NTW-2NTU). To comply with the above proton-pumping mechanism, Lanyi interprets these data to show that the SB-Wat402 Hbond is maintained in L but broken in M. In our view, the only consistent interpretation of these data is that Wat402 is disordered and the SB-Wat402 H-bond is broken in both.
Acknowledgments We thank  Thomas Ursby  for providing scripts for calculating the q-weighted difference Fourier maps presented in Fig. 5. We thank  Tsutomu Kouyama  for providing crystallographic observations associated with the wild-type bR pdb entry  1IW6. We thank  Valentin Borshchevskiy  for allowing access to structures and experimental data corresponding to entries  4MD1  and  4MD2  prior to their release by the  Protein Data Bank. We thank  Frieda Reichsman  for assistance in making Supplementary Movie 1. Financial support from the  Knut and Alice Wallenberg Foundation (KAW) , the  Swedish Strategic Research Foundation (SSF) , the  Swedish Research Council (VR) , the  European commission Marie Curie Training Network NanoMem , and from the  French National Research Agency  (Grant  ANR-11-JSV5-0009-01 ) is gratefully acknowledged.
Transcripts related to lignocellulose degradation are enriched in wood grown cultures Transcriptomes were sequenced from triplicated independent three day-cultures under three different sets of conditions:  (1)  in the presence of maltose as the solecarbon source, (2) in the presence of ground pine wood as the sole-carbon source, and (3) in the presence of ground aspen wood as the sole-carbon source. For each condition, RNAseq data quality was verified by performing qPCR on a sample set of eight genes (Additional file 3: Figure  S1 ). Expression levels were in good agreement with transcriptomic data. In total, transcriptomic analyses revealed 267 transcript sequences predicted to encode CAZymes, which were classified into 71 families of the CAZy database (http://www. cazy. org, [22] ). When applying a fourfold increase in relative transcript abundance as the significance threshold, 114 (43 %) and 105 (39 %) unique sequences were considered significantly more abundant in the samples obtained from pine and aspen, respectively, as compared to maltose (at least fourfold enrichment).
RNA-seq and subsequent data analysis Total RNA was extracted from 100 mg tissue ground with FastPrep Lysis Matrix A (MP Biomedicals) in 1 ml TRIZOL (Ambion). Nucleic acids were precipitated with isopropanol, resuspended in water and treated with RNase-free DNase I (QIAGEN). Total RNA was precipitated with LiCl and resuspended in DEPC-treated water. RNA quantity and quality were determined using the Experion RNA Std-Sens kit (QIAGEN). Double-stranded cDNAs were synthesized from Poly A RNA and fragmented (200-300 bp) before construction of the sequencing libraries (Kapa Library Amplification Kit; Kapa Biosystems). Sequencing was done on the Illumina HighSeq-2500 JGI platform generating paired end reads of 150 bp each. Raw fastq file reads were filtered and trimmed using the JGI QC pipeline. The reads obtained from each replicate; read counts and normalized read counts are available on GEO  [46]  under accession number GSE74234.
QCed reads from each library were aligned to the reference genome Pycnoporus coccineus BRFM 310 v1. 0 using TopHat  [47]  with only unique mapping allowed. Read counts were determined by HTSeq (Galaxy Tool Version 0. 3. 2). Correlation between biological replicates was evaluated using Pearson's correlation (Additional file 2: Table  S10 , Table  S11 ). Differential gene expression was analyzed on R using DESeq2 package (version 1. 5)  [48]. Gene models for which the mean raw read counts were inferior to five were considered as not transcribed and their read counts were changed to zero. Read counts were normalized using ddsNorm from the DESeq Bioconductor package. This normalization method is based on the hypothesis that most genes are not differentially expressed and should have similar read counts across samples  [49].
Characterization of secretomes using LC-MS/MS LC-MS/MS analysis of P. coccineus secretomes, PcoAspen, PcoPine and PcoMaltose, was performed as described in Ref. [50]. Briefly, short SDS-PAGE runs (pre-casted Bis-Tris Mini Gels, Invitrogen, France) were performed, allowing 10 µg of proteins diafiltered from secretomes to migrate on 0. 5 cm length. Each onedimensional electrophoresis lane was cut into two slices of gel and protein identification was performed using PAPPSO "Plate-forme d' Analyse Protéomique de Paris Sud-Ouest" platform facilities. In-gel digestion was carried out according to a standard trypsinolysis protocol. Online analysis of peptides was performed with a Q-exactive mass spectrometer (Thermo Fisher Scientific, USA), using a nanoelectrospray ion source. Protein identification was performed by querying MS/MS data against the Pycnoporus coccineus genome (http:// genome.
jgi. doe. org/Pycco1/Pycco1. home. html), together with an in-house contaminant database, using the X!Tandem software (X!Tandem Cyclone, Jouy en Josas, France). All peptides matched with an E value lower than 0. 05 were parsed with X!Tandem pipeline software. Proteins identified with at least two unique peptides and a log (E value) lower than -2. 6 were validated.
Principal component analysis Principal component analysis (PCA) was performed using Matlab software v. 7. 14. 0. 739 R2012a (The Mathworks, Inc. ) with PLS Toolbox v. 6. 7. 1 (Eigenvector Research Inc. ). Individual ToF-SIMS spectra from replicate locations on the wood powder residues were preprocessed as follows: (i) the peak intensities were normalized to the total ion intensity of the peak list to eliminate the influence of overall intensity changes that might arise from topography or variations in instrumental setup; (ii) data at each mass were mean centered so that all principal components (PCs) described variations from the data set mean.
This finding reinforces significant concerns recently expressed in the scientific literature about reproducibility and whether many false positives are being reported as fact  (Colquhoun, 2014; Rekdal, 2014; Begley & Ellis, 2012; Prinz, Schlange & Asadullah, 2011; Greenberg, 2009; Ioannidis, 2005). Data transparency and open presentation, while central notions of the scientific method along with their complement, reproducibility, have met increasing challenges as dataset sizes grow far beyond the capacity of printed tables in articles. An extreme example is the case of DNA sequencing data. This was one of the first classes of data, along with crystallographic data, for which academic publishers began to require database accession numbers as a condition of publishing, as early as the 1990's.
Why cite data? Data citation is intended to help guard the integrity of scholarly conclusions and provides a basis for integrating exponentially growing datasets into new forms of scholarly publishing. Both of these goals require the systematic availability of primary data in both machine-and human-tractable forms for re-use. A systematic review of current approaches is provided in CODATA-  ICSTI Task Group (2013). Three common practices in academic publishing today block the systematic reuse of data. The first is the citation of primary research data in footnotes, typically either of the form, "data is available from the authors upon request", or "data is to be found on the authors' laboratory website, http://example. com". The second is publication of datasets as "Supplementary File" or "Supplementary Data" PDFs where data is given in widely varying formats, often as graphical tables, and which in the best case must be laboriously screen-scraped for re-use.
The third is simply failure in one way or another to make the data available at all. Integrity of conclusions (and assertions generally) can be guarded by tying individual assertions in text to the data supporting them. This is done already, after a fashion, for image data in molecular biology publications where assertions based on primary data contained in images typically directly cite a supporting figure within the text containing the image. Several publishers (e. g. , PLoS, Nature Publications, and Faculty of 1000) already partner with data archives such as FigShare (http://figshare. com), Dryad (http://datadryad. org/), Dataverse (http://dataverse. org/), and others to archive images and other research data. Citing data also helps to establish the value of the data's contribution to research.
The Publishing Workflows group met jointly with the Research Data Alliance's Publishing Data Workflows Working Group to collect and document exemplar publishing workflows. An article on this topic is in preparation, reviewing basic requirements and exemplar workflows from Nature Scientific Data, GigaScience (Biomed Central), F1000Research, and Geoscience Data Journal (Wiley). The Common Repository APIs group is currently planning a pilot activity for a common API model for data repositories. Recommendations will be published at the conclusion of the pilot. This work is being undertaken jointly with the ELIXIR (http:// www. elixir-europe. org/) Fairport working group. The Identifiers, Metadata, and Machine Accessibility group's recommendations are presented in the remainder of this article.
" c CrossRef identifier policy reads: "The. Member shall use the Digital Identifier as the permanent URL link to the Response Page. The. Member shall register the URL for the Response Page with CrossRef, shall keep it up-to-date and active, and shall promptly correct any errors or variances noted by CrossRef. " d For example, the French National Library has rigorous internal checks for the 20 million ARKs that it manages via its own resolver. Both require persistence commitments of their registrants and take active steps to monitor compliance. DataCite is specifically designed-as its name would indicate-to support data citation. A recent collaboration between the software archive GitHub, the Zenodo repository system at CERN, FigShare, and Mozilla Science Lab, now makes it possible to cite software, giving DOIs to GitHub-committed code  (GitHub Guides, 2014).
Identifiers. org Uniform Resource Identifiers (URIs) Many common identifiers used in the life sciences, such as PubMed or Protein Data Bank IDs, are not natively Web-resolvable. Identifiers. org associates such database-dependent identifiers with persistent URIs and resolvable physical URLs. Identifiers. org was developed and is maintained at the European Bioinformatics Institute, and was built on top of the MIRIAM registry  (Juty, Le Novére & Laibe, 2012). Identifiers. org URIs are constructed using the syntax http://identifiers. org/ <data resource name>/<native identifier>, where <data resource name> designates a particular database, and <native identifier> is the ID used within that database to retrieve the record. The Identifiers. org resolver supports multiple alternative locations (which may or may not be mirrors) for data it identifies.
Landing pages The identifier included in a citation should point to a landing page or set of pages rather than to the data itself  (Hourclé et al. , 2012; Rans et al. , 2013; Clark, Evans & Strollo, 2014). And the landing page should persist even if the data is no longer accessible. By "landing page(s)" we mean a set of information about the data via both structured metadata and unstructured text and other information. There are three main reasons to resolve identifiers to landing pages rather than directly to data. First, as proposed in the JDDCP, the metadata and the data may have different lifespans, the metadata potentially surviving the data. This is true because data storage imposes costs on the hosting organization. Just as printed volumes in a library may be de-accessioned from time to time, based on considerations of their value and timeliness, so will datasets.
The JDDCP proposes that metadata, essentially cataloging information on the data, should still remain a citable part of the scholarly record even when the dataset may no longer be available. Second, the cited data may not be legally available to all, even when initially accessioned, for reasons of licensing or confidentiality (e. g. Protected Health Information). The landing page provides a method to host metadata even if the data is no longer present. And it also provides a convenient place where access credentials can be validated. Third, resolution to a landing page allows for an access point that is independent from any multiple encodings of the data that may be available. Landing pages should contain the following information. Items marked "conditional" are recommended if the conditions described are present, e.
g. , access controls are required to be implemented if required by licensing or PHI considerations; multiple versions are required to be described if they are available; etc. • (recommended) Dataset descriptions: The landing page must provide descriptions of the datasets available, and information on how to programmatically retrieve data where a user or device is so authorized. (See Dataset description for formats. ) • (conditional) Versions: What versions of the data are available, if there is more than one version that may be accessed. • (optional) Explanatory or contextual information: Provide explanations, contextual guidance, caveats, and/or documentation for data use, as appropriate. • (conditional) Access controls: Access controls based on content licensing, Protected Health Information (PHI) status, Institutional Review Board (IRB) authorization, embargo, or other restrictions, should be implemented here if they are required.
Best practices for dataset description Minimally the following metadata elements should be present in dataset descriptions: • Dataset Identifier: A machine-actionable identifier resolvable on the Web to the dataset. • Title: The title of the dataset. • Description: A description of the dataset, with more information than the title. • Creator: The person(s) and/or organizations who generated the dataset and are responsible for its integrity. • Publisher/Contact: The organization and/or contact who published the dataset and is responsible for its persistence. • PublicationDate/Year/ReleaseDate: ISO 8601 standard dates are preferred  (Klyne & Newman, 2002). • Version: The dataset version identifier (if applicable).
ACKNOWLEDGEMENTS We are particularly grateful to  PeerJ Academic Editor Harry Hochheiser  ( University of Pittsburgh ), reviewer  Tim Vines  ( University of British Columbia ), and two anonymous reviewers, for their careful, very helpful, and exceptionally timely comments on the first version of this article. Many thanks as well to  Virginia Clark  ( Université Paul Sabatier ),  John Kunze  ( California Digital Library ) and  Maryann Martone  ( University of California at San Diego ) for their thoughtful suggestions on content and presentation.