dataesr/scientific-paragraphs-categorization huggingface dataset:
Prediction of peptidic features Putative mature Kiss-peptides of various lengths were deduced after the prediction of proteolytic cleavage site from the translated ORF encompassing Kp  (10). These putative proteolytic cleavage sites were predicted using NeuroPred tool  [60]. The 7 transmembrane domains of the predicted KissR were determined using TMHMM software (TMHMM Server v. 2. 0).
Phylogenetic analysis Kiss phylogeny 68 sequences, from 33a. a. to 65a. a. , and each one composed of a predicted mature Kisspeptin followed by its proteolytic cleavage and alpha-amidation site, were first aligned using ClustalW  [61] , then manually adjusted. The JTT (Jones, Taylor and Thornton) protein substitution matrix of the resulting alignment was determined using ProTest software  [62]. Phylogenetic analysis of the predicted mature Kisspeptin alignment was performed using the neighbour joining method (MEGA 5. 1 software), with 1,000 bootstrap replicates.
KissR phylogeny Amino-acid sequences of 66 known or predicted KissR were first aligned using ClustalW  [61] , then manually adjusted. The JTT (Jones, Taylor and Thornton) protein substitution matrix of the resulting alignment was determined using ProTest software  [62]. Phylogenetic analysis of the KissR sequence alignment was performed using the maximum likelihood method (RaxML software  [63] ), with 1,000 bootstrap replicates.
Syntenic analyses Synteny maps of the conserved genomic regions in human, chicken, zebra finch, Chinese turtle, green anole, Xenopus, coelacanth and spotted gar were performed using the PhyloView of Genomicus v71. 01 web site (http://www. genomicus. biologie. ens. fr/genomicus-71. 01/ cgi-bin/search. pl) [64]. The analysis of the neighbouring genes of the four coelacanth KissR paralogs was completed by manual gene annotation of the coelacanth genome. The analyses of the mallard duck and painted turtle genomic regions were performed using the preliminary gene annotations of the genome assembly duck1 and ChrPicBel3. 0. 1 generated by Ensembl release 71. The synteny analyses of rock pigeon, alligator, garial and crocodile conserved genomic regions were obtained performing TBLASTN (CLC DNA Workbench 6 software) searches in the corresponding genomic databases and for all the conserved genes of the Kiss and KissR syntenies.
The vectors were then transfected in One Shot® TOP10 Chemically Competent E. coli (Invitrogen). After the bacteria containing a vector with insert had grown in miniprep cultures, vectors were extracted and purified using QUIAquick Spin Miniprep Kit (Qiagen, Hilden, Germany). Their inserts were then sequenced at GATC biotech Ltd (Konstanz, Germany). The obtained sequence was submitted to EMBL under the accession number: HG328246.
Acknowledgements We thank  Pr. H. Tostivint ,  MNHN , for his helpful comments and  Dr A. Virmani  for English corrections. We thank all the different consortiums at the initiative of sequencing, assembly, annotation, publication and update of genomic and transcriptomic databases. Our thanks also include the authors of all web sites providing free access to their genomic databases, including the Ensembl genome browser web site, NCBI genome browser web site and the croc genomes web site. We thank the authors of the Genomicus web site providing a very useful and friendly tool for synteny analysis.
Significant mass transfer did happen in this system, however, the mass of the most evolved star being less than half the mass of its companion. It is not possible to always obtain as many data as in the case of SS Lep (e. g. , in most symbiotic systems, the hot star would not have a signature in the infrared) and thus to constrain as much the system. However, there are several systems for which it is possible to determine, with great accuracy, the diameter of the mass-losing giant. This, combined with previous data, could already answer the critical question raised above and more particularly, constrain the Roche lobe filling factor. Using the PIONIER/VLTI interferometric instrument, we have measured therefore the diameter of several symbiotic and related stars. The observations are presented in Sect.
We provide in the online Table  7  the list of calibrators used. Data reduction was done in the usual way with the pndrs package presented by Le  Bouquin et al. (2011)  and the LITpro software 2   (Tallon-Bosc et al. , 2008)  was used to fit a uniform disc to the visibilities and closure phases. Our results are shown in Figs. 1  and 2 , as well as in Table  1. As can be seen in this table, where the last column indicates the resulting reduced χ 2 , for all stars but HD 352, the assumption of a uniform disc leads to a very good fit. The stars that are studied in this paper are all known to be single-lined spectroscopic binaries and it is thus safe to assume that there should be no contribution from the companion to the total flux. This is even more so in the H-band, as the companion is always a hot star.
Identification of vertebrate Tshb and Tshr sequences Blast analyses  [30]  were performed on-line using protein as query (tBlastn) on NCBI (http://blast. ncbi. nlm. nih. gov/Blast. cgi), Ensembl (http://www. ensembl. org/Multi/blastview), DDBJ (http://blast. ddbj. nig. ac. jp/), as well as on web sites for little skate (Skatebase: http://skatebase. org/skateBLAST and elephant shark (http://esharkgenome. imcb. a-star. edu. sg/blast/). Eel sequences were identified from European and Japanese eel genomes available on the website Eel Genome of ZF-Genomics (http:// www. zfgenomics. org/sub/eel) in addition to the assembly available in NCBI, using the CLC BIO software (Qiagen, Denmark). Protein sequences were predicted from retrieved genomic or Expressed Sequence Tag (EST) sequences by using consensus splice donor and acceptor site and by sequence identity comparison with related Tshb or Tshr genes (Table  S1  and Table  S2 ).
Phylogenetic and syntenic analyses Alignments were fitted manually using Se-AL editor (http:// tree. bio. ed. ac. uk/software/seal/). The phylogenetic reconstructions were performed on-line by using a maximum likelihood method with PhyMyL 3. 0 software  [31]  on the website file (http:// www. phylogeny. fr/) with HKY85 as substitution model for TSHb-related nucleotide sequences and WAG for TSHR-related amino-acid sequences and default settings for the other parameters. The robustness of the reconstruction was estimated by the aLRT score and/or by bootstrapping over 500 replicates. Nucleotide sequences of the entire coding region (including signal peptide) were used for Tshb subunits with truncation in the 39 end of the longest sequences. The amino acid sequences were used for the TSHR tree reconstruction.
Mapping the genomic neighborhoods of Tshb and Tshr genes were performed with region overview on Ensembl, NCBI and EBI genome browsers and for the Elephant shark genome on the specific Ensembl website (http://ensembl. fugu-sg. org/index. html). Flanking genes of duplicated Tshb and Tshr were identified and annotated in the eel from the eel genome databases, using CLC BIO software.
Moreover, in each case, we checked that the isolated cDNAs of one of the duplicated genes could not be amplified by the primer set corresponding to the other duplicated gene. Messenger RNA was quantified on LightCycler using the LightCycler FastStart Master plus Sybr green I kit (Roche, Mannhein, Germany) as recommended by the manufacturer. The final primer concentration used was 500 nM. Each sample was run in duplicate using a 1/5 cDNA dilution. The PCR conditions were 95uC for 10 min followed by 50 cycles at 95uC for 5 sec, 60uC for 10 sec and 72uC for 10 sec. The specificity of amplified product was checked by melting curve analysis after the amplification reactions. Relative transcript abundance was calculated from standard curves prepared from pituitaries and thyroid follicles cDNA using LightCycler software.
In stickleback, Tshb and Tshb3 expression was compared only in the pituitary where both are expressed but Tshb3 showed differential transcriptional regulation according to the ecotype  [18]. Unlike in the eel, the classical Tshb subunit was shown to be expressed not only in the pituitary but also in the gonads of the fathead minnow  [51]  and the grouper  [52]. EST data mining indicates that Tshb transcripts are expressed in the brain of several teleost species (zebrafish -EH470445. 1 and goldfish -DY231942; tilapia -GR616157. 1; medaka -DK0206541) unlike the eel. In particular, Tshb transcripts are found in the saccus vasculosus, at the base of the hypothalamus in salmon and may be involved as a photoperiodic signal transducer  [53]. It is too early to draw conclusions about the absence of significant expression of the classical TSH in other tissues than the pituitary in the eel.
The Global Field Model of CR 2064 The global coronal magnetic field of CR 2064 is modelled using a PFSS approach. These models assume a current-free coronal field with an observationally prescribed and/or modelled boundary condition at the photosphere. PFSS models assume that the field becomes purely radial at a given height called the source surface: a free parameter usually set to the value 2. 5 R. The PFSS model used in this article (see Figure  3 ) was computed with the Finite Difference Iterative Potential-Field Solver (FDIPS) code described by  Tóth, van der Holst, and Huang (2011) , using the MDI synoptic magnetogram for CR 2064 as photospheric boundary condition. Individual full-disc MDI magnetograms are built every 96 minutes. The calibrated photospheric line-of-sight (LOS) field is transformed into the total field strength, assuming the magnetic-field vector is fully radial at the location of the measurement.
Therefore, we look for sources of sporadic emission at 150. 9 MHz, which is the lowest NRH frequency and the one which most likely shows signatures of Type I bursts. We analysed the brightness distribution over the solar disc on 13 December with a temporal cadence of one second, choosing the time interval for which the ionospheric effects would be minimal (12:30 -13:40 UT). We verified that this was the case by looking at the East-West and North-South one-dimensional brightness distribution diagrams (http://www. secchirh. obspm. fr/index. php) at 150 and 432 MHz for this day. In addition to the enhanced emission over the AR we observed the existence of regions where the emission fluctuates, increasing and decreasing recurrently, as shown in Figure  9. To determine the appearance of these sporadic sources in a more systematic way, we used the specific software developed for NRH data analysis that is included in the Solar-Soft package.
Furthermore, to understand the full process, studies such as the one presented here need to be complemented by a detailed analysis of several parameters observed in-situ (i. e. plasma velocity, density, composition, and magnetic field) together with the determination of the outflowing-plasma composition. project). LvDG and DB acknowledge support by STFC Consolidated Grant ST/H00260/1. LvDG's work was supported by the Hungarian Research grant OTKA K-081421. CHM, AMV, and GDC are members of the Carrera del Investigador Cientí fico (CONICET). FAN is a fellow of CONICET. We thank D. M. Long for the enhanced XRT image and H. Morgan for the XRT processing software.
Acknowledgements CHM and GDC acknowledge financial support from the  Argentinean  grants  PICT 2007-1790  ( ANPCyT ),  UBACyT 20020100100733 , and  PIP 2009-100766  ( CON-ICET ). The research leading to these results has received funding from the  European Commission 's  Seventh Framework Programme  under the grant agreement No. 284461  (eHEROES.
The pellets were treated with RNase (Ambion, 20 µg/mL) and DNase (Invitrogen, 10 U/µL) (both from Life Technologies, Grand Island, NY, USA) to concentrate the viral material. RNA and DNA were extracted separately, and a random reverse transcription PCR was performed, as described (  6 ), to generate unbiased PCR products of ≈300 bp. High-throughput sequencing was performed by using a MiSeq platform (Illumina, San Diego, CA, USA). A total of 476,430 sequences were generated (Table  1 ), 10. 8% of which matched with known viral sequences, as determined by using GAAS software (http://gaas. sourceforge. net/) (7)  with an expected value of 10 -3 ; 7. 5% of the eukaryotic viral reads were similar to avian CoVs, such as turkey CoV (TCoV) and infectious bronchitis virus (IBV). A total of 1,444 reads related to CoVs were aligned against the most similar TCoV genome available in GenBank (TCoV/CA/MG10; accession no.
EU095850). The reads fairly aligned to almost the whole TCoV genome; the overall coverage was 78. 86% (data not shown). A CoV-specific reverse transcription PCR was performed and the result was positive, specifically in intestinal tissues of experimentally infected birds (Table  2 ) (8). Furthermore, immunochemistry was performed by using a monoclonal antibody specific for TCoVs  (9). We observed an intense, cytoplasmic, and granular labeling in enterocyte villi of inoculated birds only (Figure  1 ), suggesting a substantial intestinal replication of a TCoV-related virus. A 3,680-nt consensus full sequence of the spike (S) gene was completed by classical PCR and Sanger sequencing (GenBank/EMBL accession no. HF544506). A BLAST (http://blast. ncbi. nlm. nih. gov/Blast. cgi) search followed by a phylogenetic analysis performed on the complete S gene showed that guinea fowl fulminating enteritis virus corresponds to a distinct genotype of CoV, clustering within Gammacoronavirus genus, which also includes TCoV and IBV  (10).
Acknowledgments We thank  Simon Roux  for help with bioinformatics. E. L. is supported by a grant from the  French Ministry of Agriculture and Region Midi-Pyrénées. This project was supported by the  French Comité Interprofessionnel de la Pintade  and by the  French Ministry of Agriculture. Mr Liais  is a PhD candidate in virology at the  Host-Pathogen Agents Interactions Joint Research Unit, National Veterinary School , and  INRA, Toulouse, France. His research interests are the host interactions of avian influenza viruses and metagenomic approaches in virology.
However, the stumbling block of in silico approaches is that they are built from the available knowledge: not all is known about everything. Nevertheless, an impressive and ever increasing amount of biological knowledge is already available in the scientific literature, databases and knowledge bases such as, to name a few, DrugBank  [31] , KEGG  [32] , PharmGKB  [33] , Reactome  [34]  and TTD  [35]. In addition to the difficulty of integrating an increasing body of knowledge comes the inherent complexity of biological systems themselves  [36] : this is where computational tools can help owing to their integrative power  [37] [38] [39]. This interplay between wet lab and computational biology is synergistic rather than competitive  [40]. Since wet lab experiments produce factual results, they can be considered as trustworthy sources of knowledge.
Patients and human samples We enrolled 121 HCM index cases without mutations in MYH7, MYBPC3, TNNT2, TNNI3, or MYL2 (data not shown). They were selected out of 299 HCM index cases recruited from the Eurogene Heart Failure cohort supported by the Leducq Foundation  [19, 21]. Diagnosis was grounded on medical history, physical examination, electrocardiogram, and echocardiogram (left ventricle (LV) wall thickness C15 mm in probands and [13 mm in relatives)  [8] [9] [10]. Controls consisted of 262 individuals. Human myocardial samples were obtained from HCM patients who underwent septal myectomy or heart transplantation, from a patient undergoing aortic valve implantation due to aortic stenosis, and from individuals who had no cardiac disease but died of another cause. All materials from patients and controls were taken with informed consent of the donors and with approval of the local ethical boards.
Screening of FHL2 for genetic variants FHL2 gene has eight exons, of which five (exons 4-8) are coding. There are four FHL2 variants mainly differing in the 5 0 UTR, but encoding the same isoform. Therefore, only the five coding exons for FHL2, including neighboring intron boundaries were screened by PCR amplification performed on 30 ng of genomic DNA from peripheral lymphocytes using specific primer pairs (Supplemental Table  2 ). Sequences were examined using Codon Code Aligner Software Ò. Reference FHL2 sequence was taken from NCBI (NG_008844. 2) with ?1 designing the A of the ATG codon. Rat cardiac myocytes culture, transduction, and hypertrophy stimulation Isolation of neonatal rat cardiac myocytes (NRCMs) and stimulation with hypertrophy stimuli, followed by subsequent automated cell size determination was performed as defined previously  [29].
Statistical analysis Data are presented as mean ± SEM. Statistical analyses were performed by one-way or two-way ANOVA followed by Dunnett's or Bonferroni's post test, and by Student's t test as indicated in the figure legends, using the GraphPad software (GraphPad Software), version 5. 02. A value of P \ 0. 05 was considered significant. Quantitative PCR data analyses were carried out using the DDCt method.
5 %; rs1131188481) in the NHLBI Exome variant server (http:// evs. gs. washington. edu/EVS/), a freely available database comprising about 13,006 alleles of European American and African American populations. In silico analysis using the prediction programs Mutation Taster (http://www. mutationtaster. org) and PolyPhen-2 (http://genetics. bwh. Finally, variants IV-VI were detected in the cohort but are known to be FHL2 synonymous polymorphisms (Fig. 2 , Online Table  1 ). Variant IV is a c. 678C[T transition in exon 7 (p. Asn226Asn (N226N)), which was also found in 1/262 control individuals. Frequency in the NHLBI Exome variant server is 126 in 13,328 alleles (1 %; rs137869171). Variant V is a c. 804C[T transition in exon 8 (p. Asp268Asp (D268D)) with a frequency of 9 % in the Exome variant server (rs3087523).
Acknowledgments We are thankful to family members for collaboration. We would like to thank  M. Komajda  ( Paris ) for continuous support in the  Eurogene Heart Failure network, M. Hirt (Hamburg)  for fruitful discussion. We would also like to thank  A. Eder ,  I. Vollert ,  C. Neuber  and  A. Sto  ¨hr ( Hamburg ) for help in contractility experiments,  E. Kraemer  and  S. Schlossarek  ( Hamburg ) for isolation of human ventricular RNA, and  Charles Redwood (Oxford)  for DNA sequencing of human HCM tissue samples. Funding sources: This work was supported by the  Leducq Foundation (Eurogene Heart Failure) ,  the seventh Framework Program  of the European Union (Health-F2-2009-241577- Big-Heart  project), and the  Association Institut de Myologie (Paris).
Bioinformatics and statistics The non-parametric test Mann-Whitney U test was used to assess differences in age and sex between the patient and control groups. Data quality control was performed using the Genome Studio software (Illumina) according to instructions  [18] , and Simca P+ software (Umetrics, Umea ˚, Sweden). Samples that were obvious outliers according to Hotelling's T2 values  [19]  in the cluster analysis and PCA analysis were removed from further analysis. To determine differentially expressed genes data were analyzed using Genome Studio software. Data were normalized using cubic spline with background correction. As error model Illumina custom was used. Probes with average signal 550, detection p value 40. 05 or fold change5±1. 5 were filtered away. Benjamini Hochberg False Discovery Rate (FDR) correction for multiple testing was used and only the tests of difference in expression with a q value50.
05 were considered significant. ErmineJ software (http://erminej. chibi. ubc. ca/) [20]  was used for the gene list analysis. The software uses Gene Ontology (GO) terms as gene lists and gene score resampling was used as a method for analyzing significant gene lists. To be classified as significant each gene list had to have a FDR under 0. 05 and a multifunctionality score under 0. 80. Principal component analysis (PCA) is an unsupervised projection method that was applied to the data set to try to cluster samples with similar gene expression profiles. PCA models were created using the Simca P+ software (Umetrics). For the analysis, the entire data set was used but filtered to remove probes mostly displaying background noise. All probes with signal average 550, and detection p value40. 05 were removed.
Functional pathways of significant genes To determine which pathways are most affected in ATTR patients' liver, gene lists analysis using GO terms was performed. When comparing patients to controls six ontologies were still significant after correction with FDR. The two ontologies with the most significant p values were Protein folding and Endoplasmic reticulum lumen (Table  2 ). Similar results were obtained when doing PCA analysis on the ontologies (data not shown). Gene list analysis on data from fat biopsies was not done since the number of differentially expressed genes was so low.
Method Seven people participated. The authors (DL and AH) and GS knew the experimental hypotheses. The tasks of duration judgment, SJ, and TOJ were tested in different sessions. Observers conducted first the duration judgments, then the SJ and finally the TOJ. The sole exception was AH, who conducted some more sessions of duration judgments after the TOJ. For the duration judgments, two standard durations (see below) were tested in different sessions whose order was pseudo-randomized across observers. For each standard, observers completed between 280 and 1,120 trials. For SJ and TOJ, each observer completed 220 trials. The data and code (in R,  R Core Team, 2014)  to do the statistical analysis and create the figures are available at http://www. dlinares. org. The visual and auditory stimuli were generated using PsychoPy  (Peirce, 2007).
Studying object recognition is central to fundamental and clinical research on cognitive functions but suffers from the limitations of the available sets that cannot always be modified and adapted to meet the specific goals of each study. We here present a new set of 3D scans of real objects available on-line as ASCII files, OB3D. These files are lists of dots, each defined by a triplet of spatial coordinates and their normal that allow simple and highly versatile transformations and adaptations. We performed a web-based experiment to evaluate the minimal number of dots required for the denomination and categorization of these objects, thus providing a reference threshold. We further analyze several other variables derived from this data set, such as the correlations with object complexity.
This initial set has subsequently been expanded and modified, and norms have been established for different language speaking communities (for a review see  Brodeur et al. , 2010) , thus expanding the meta-data associated with these databases  (Alario and Ferrand, 1999; Rossion and Pourtois, 2004). Recent modifications aimed at reducing stimulus information for testing specific processes related to visual recognition and object identification. For instance, De  Winter and Wagemans (2004)  used silhouettes, degraded, fragmented, and straight-line versions of pictures to evaluate the limits of contour-based integration and segmentation of nameable objects. Other visual data sets are often made up from photographs transformed into different numerical formats. Efforts were made to provide well-controlled sets  (Bonin et al.