dataesr/scientific-paragraphs-categorization huggingface dataset:
Semantics for HCLS An overwhelming amount of HCLS knowledge is represented in natural language, information models, clinical repositories (databases), ontologies for terminologies, vocabularies, etc. Additionally, the involvement of various stakeholders, such as hospitals, healthcare standards, pharmacy, patients, multiplies the integration complexity of this domain. Intelligent processing, logical aggregation of information, synthesis and analysis, and the development of knowledge systems that can serve purposeful ends are needed. HCLS has been one of the primary field of application for knowledge representation and reasoning systems. In the past researchers have tried to formalize and integrate the knowledge bases in HCLS systems and many of the successful systems in earlier times were centralized and limited to sub domain or particular application of a HCLS domain  (Szolovits, 1982; Kashyap & Sheth, 1996).
Introduction Nowadays, Health Care and Life Sciences (HCLS) systems are facing challenges to bring healthcare stakeholders together, such that healthcare resources (e. g. , data, schema, and applications) are seamlessly accessed across all related domains. Knowledge and HCLS specialists have advocated the use of semantics to (1) create interlinked networks of HCLS resources and (2) overall management and integration of HCLS resources. Ontology Based Information Systems (OBISs) have recently received attention for their flexibility and automation in maintaining, updating, exchanging schemas and underlying data. This strength is due to the fact that schema and data are loosely-coupled (as compared to cohesively-weak schema and data in traditional databases) and both represented and integrated in a logical fashion.
Database-Style Integrity Constraints for OWL This approach is motivated by data-centric problems in DL/OWL based applications. The authors of  (Motik, Horrocks, & Sattler, 2007)  have established the relationship between the role of Integrity Constraints (IC) in databases, i. e. , (1) data reasoning (e. g. , in checking the integrity of a database) and schema reasoning (e. g. , in computing query subsumption), and (2) DL/OWL knowledge bases (e. g. , schema (TBox ) reasoning and data (ABox ) reasoning). In this approach an additional TBox is introduced to model constraint axioms, which results in the knowledge base containing two TBoxes and an ABox. In TBox reasoning, constraints behave like normal TBox axioms, and for ABox reasoning they are interpreted as constraints in relational databases.
Query-Based Data Translation The query-based approach translates data from one knowledge source to another, and is close to the problem of expressing complex correspondences of the example-scenario presented in this chapter. In this approach mappings between ontologies are first expressed in expressive alignment language  (Euzenat, Scharffe, & Zimmermann, 2007)  and then grounded and executed to a combined query language and engine, SPARQL++ and PSPARQL, called PSPARQL++  (Euzenat, Polleres, & Scharffe, 2008). Listing 1. 7 show how (a) two ontology entities (guh:orderDate, guh:time) could be concatenated to a single entity (dc:date) and (b) a conversion is possible between an object property and a datatype property by using proposed cast-function that converts xsd:string to RDF resource. Expressive correspondences between ontology instances can be constructed using "SPARQL CONSTRUCT" to create additional dataset and query upon them.
, 2004)  improves on this by treating context identifiers as any other RDF resource identifiers: they are URIs that can be dealt with as first class objects. The case of query-based transformations is a bit particular because the transformation must say from which and to what datasets the translation occurs, but the transformation could actually be used independently of the context. This explains the +/-sign for this formal approach. Modular rule bases uses a mechanism similar to the one of DDL etc but the underlying formalism is not based on Semantic Web languages. Modularity is almost always associated with context awareness. This is because in order to reuse modules, one must be able to identify them, that is, have a mean of identifying the provenance of knowledge. Moreover, formalisms such as DDL, E-connections, P-DL, IDDL are designed to enable the reuse of external knowledge through the use of cross-context assertions like imports, bridge rules, links, correspondences.
Of course, it is possible to use existing languages-such as RDF and OWL as in  (Kolovski, Parsia, Katz, & Hendler, 2005) -to represent policies but OWL cannot formally distinguish between ontological axioms and policy axioms. This is true for most of the formalisms presented here. Notable exceptions are Defeasible Logic Programs for which there is a distinction between "strict" knowledge, which is always true, and "defeatable" knowledge which can be canceled by way of an automatic argumentation process. Policies are typically defeatable by stronger policies (e. g. , from GUH's point of view, GOET's policy axioms would be defeated by contradicting local policies). As an alternative, OWL/IC offers a way to separate the usual ontological knowledge from database-style constraints. Unfortunately, both approaches are unable to distinguish the context in which appear the axioms or policies.
Ontology engineering is in itself a whole research field which gained momentum with the development of the Semantic Web. Yet, extending the ontology formalisms would also require updating the engineering methods that are mostly developed specifically for OWL  (Cristani & Cuel, 2005). For practitioners, explaining inference results is required. Second, it can be hypothesised that not all systems will ever use a unique data model. It is thus important to rely on data conversion. For instance, the transformation of syntactic to semantic data format (and vice-versa) is the first basic step in exploring implicit semantics within syntactic data. Initiatives like RDB2RDF 22  , GRDDL 23 , are improving this transformation and help taking advantage of legacy-database within the framework of the Semantic Web.
MATERIAL AND METHODS Sampling A panel of French GPs was constituted in June 2010. Its procedures have already been described elsewhere. 4 riefly, 5170 GPs were selected by random sampling from the Ministry of Health's exhaustive database of health professionals in France. Sampling was stratified for location of the general practice (urban, peri-urban or rural areas), gender, age (<49, 49-56, >56 years old) and the number of consultations (<2849, 2849-5494, >5494) in 2008. Of the 3888 contacted and eligible GPs, 1431 (36. 8%) agreed to participate in the panel, that is, to provide regular data on their activity and respond to five consecutive surveys on different topics during a 30-month period. Among the 1136 GPs who participated in the fifth national cross-sectional survey, conducted in November 2012 (attrition rate between the first and fifth cross-sectional surveys: 20.
Standards in Genomic Sciences TAS  [11] [12] [13]  Class Bacilli TAS  [14, 15]  Current classification Order Bacillales TAS  [16, 17]  Family Bacillaceae TAS  [16, 18]  Genus Bacillus TAS  [16, 19, 20]  Species Bacillus massiliogorillae IDA Type strain G2 Figure  1. Phylogenetic tree highlighting the position of Bacillus massiliogorillae strain G2 T relative to other type strains within the Bacillus genus. GenBank accession numbers are indicated in parentheses. Sequences were aligned using CLUSTAL X (V2), and phylogenetic inferences obtained using the maximumlikelihood method within the MEGA 5 software  [22]. Numbers at the nodes are percentages of bootstrap values obtained by repeating the analysis 1,000 times to generate a majority consensus tree. Clostridium botulinum was used as outgroup.
5% tri-fluoracetic-acid, and allowed to dry for five minutes. Measurements were performed with a Microflex spectrometer (Bruker Daltonics, Leipzig, Germany). Spectra were recorded in the positive linear mode for the mass range of 2,000 to 20,000 Da (parameter settings: ion source 1 (IS1), 20 kV; IS2, 18. 5 kV; lens, 7 kV). A spectrum was obtained after 675 shots at a variable laser power. The time of acquisition was between 30 seconds and 1 minute per spot. The 12 G2 T spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against 6,252 bacterial spectra including 199 spectra from 104 Bacillus species, used as reference data, in the BioTyper database. The method of identification included the m/z from 3,000 to 15,000 Da.
For every spectrum, 100 peaks at most were taken into account and compared with spectra in the database. A score enabled the identification, or not, from the tested species: a score > 2 with a validated species enabled the identification at the species level, a score > 1. 7 but < 2 enabled the identification at the genus level; and a score < 1. 7 did not enable any identification. For strain G2 T , the scores obtained ranged from 1. 177 to 1. 343, thus suggesting that our isolate was not a member of a known species. We incremented our database with the spectrum from strain G2 T (Figure  4 ). Spectrum differences with other of Bacillus species are shown in Figure  5.
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the genus Bacillus, and is part of a "culturomics" study of the gorilla flora aiming at isolating all bacterial species within gorilla feces. It was the 61 st genome of a Bacillus species and the first genome of Bacillus massiliogorillae sp. nov. A summary of the project information is shown in Table  2. The Genbank accession number is CAVL000000000 and consists of 66 large contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [29].
Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal  [30]  with default parameters but the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank database  [31]  and the Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAScanSE tool  [32]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [33]  and BLASTn against the GenBank database. ORFans were identified if their BLASTP E-value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05. Standards in Genomic Sciences To estimate the mean level of nucleotide sequence similarity at the genome level between B.
Patients Liver allograft recipients at the University of Pittsburgh Medical Center  (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) ; IRB# PRO10110393) were extracted from the EDIT database based on a histopathological-coded diagnosis of ''plasma-cell-rich hepatitis (PCH)'' or ''autoimmune-like hepatitis,'' which in turn, was based primarily on the histopathologic findings, as follows. PCH cases showed a ''hepatitic'' pattern of injury, characterized by mononuclear portal inflammation with necro-inflammatory-type interface activity where plasma cells comprised an estimated !30% of the total infiltrate, comparable to native livers with AIH  (6). Patients who underwent transplantation for AIH, as well as those with posttransplant biliary strictures or other technical complications that might contribute to an unexplained chronic hepatitis in the histopathology, were excluded.
High-resolution whole-slide imaging Slides were scanned on a Zeiss MIRAX MIDI whole-slide image (WSI) scanner (Carl Zeiss, Jena, Germany) and quantified using in-house developed IAE-NearCYTE WSI Analysis software  (19). Images correspond to WSI scans generated using a 40Â objective (0. 95 NA) with resultant image resolution of 0. 116 microns/pixel 2.
All kidney allograft biopsies were also re-reviewed to ensure the presence of a dense interstitial infiltrate contained >30% plasma cells; the majority contained a higher percentage. The absolute number and ratio of IgG4þ plasma cell/total plasma cells were determined identically to the liver analysis, except that the high-power fields were selected from the renal cortical interstitium. For the CD4þ/FOXP3þ Qdot analysis, CD4þ/FOXP3þ cells and CD4þFOXP3À cells were counted within portal tracts as previously described, and quantified manually using IAE-NearCYTE software tools. Analysis for the FOXP3þ single immunohistochemistry was performed in the same fashion. The biopsy samples were also assessed for key morphological features associated with IgG4-related disease in the general population including: (1) dense lymphoplasmacytic infiltrates combined with a storiform pattern of fibrosis, (2) increased number of IgG4þ plasma cells, (3) obliterative phlebitis and (4) mild-to-moderate eosinophil infiltrates  (23).
Statistical analysis Data were shown as mean AE SD or median. Groups were compared using the Fisher test, and Wilcoxon rank-sum (Mann-Whitney) as appropriate. Exact Chi-squared analysis was performed to compare the proportion of patients, within each cohort, with IgG4 >25 cells/high-power field (HPF) and IgG4þ cells/plasma cells >25% (based on the sensitivity/specificity) to similar patients in the other cohorts. Analyses were performed using the SAS 9. 2 software. Differences between groups were considered significant at p < 0. 05.
Event Generation and Simulation Kinematics are simulated using RESBOS  [1]  which is a next-to-leading order generator including non-perturbative effects at low boson p T  [4]. The PDFs used in RESBOS, are CTEQ6. 6 [3]. They affect the W boson mass measurement through their effects on the kinematics of decay charged leptons. The dominant effect from QED radiation to the W boson mass measurement comes from radiation of photons from the final state charged lepton. These processes are simulated by combining the PHOTOS program  [2]  with RESBOS. The techniques used by CDF and DØ Collaborations to determine the single most important ingredient, namely the lepton energy scale are very different. The CDF measurement exploits precise measurements of track momenta in the inner tracker, while the DØ mesurement relies on a detailed understanding of electron showers in the calorimeter.
Genome assembly Two independent assemblies were built with all sequence data, using the Newbler (Roche) and PCAP 41 algorithms from ~19. 6× total sequence coverage in whole-genome shotgun reads, a combination of 12× fragments, 9× 3kb, 0. 38× 20kb and 0. 02× BAC-end read pairs. A merged assembly was achieved by assigning the Newbler assembly as the reference and aligning the PCAP assembly via BLAT followed by assimilation of all aligned scaffolds using an established graph accordance method  42. Assembly consensus base error correction was accomplished by aligning Illumina reads (75 base paired-end reads, insert size 200bp), the same DNA source used for the reference, to the reference assembly using the Genomics Workbench v. 4. 03 software (CLC Bio). A consensus sequence was then created that factored the quality scores of both the reference assembly and the individual Illumina reads.
Each mRNA sample was sequenced on an Illumina GAII sequencer (60 bp). The X. maculatus transcriptome was assembled combining sequences from several tissues including heart, liver, brain, ovaries, and testes, as well as from embryonic stages 15 and 25. For the X. hellerii transcriptome, RNA from 1 month old whole fish, and from brain, liver, ovaries and testes of mature fishes was sequenced and assembled. The transcriptome sequences were aligned to the genome assembly contigs using Bowtie  43  , then assembled using the Velvet 44 /Oases package (http://www. ebi. ac. uk/ ~zerbino/oases/), reporting putative transcripts and splice variants using a coverage cutoff of 4, an insert length estimate of 120, and other parameters at default values.
Gene models and annotation Gene annotation using Ensembl genebuild was done on assembly Xipmac4. 4. 2 (GenBank Assembly ID GCA_000241075. 1; http://www. ncbi. nlm. nih. gov/genome/assembly/? term=GCA_000241075. 1 The annotated platyfish genome can be found at http:// www. ensembl. org/Xiphophorus_maculatus/Info/Index. Another gene identification analysis was performed by a combination of gene prediction and transcriptome integration. We used ab initio modeling with Augustus 45 that had been trained on the medaka gene set and on the alignment of full-length gene models of medaka and zebrafish (both from Ensembl) using BLATX  46. Transcriptome sequences were aligned to the assembly scaffolds using Bowtie  43  , then this alignment was adjusted for the most likely exon-intron boundaries using TopHat  47  , and then gene models created using Cufflinks  48.
Only those transcripts containing a complete ORF and a transcript read coverage of at least 3× were retained, and then these were reconciled into a single set of 33,756 unique potential protein-encoding genes. These gene models were further culled to a subset of 17,783 that are amenable to phylogenetic analysis for entry into a whole genome evolutionary interpretation using the PHRINGE (Phylogenetic Resources for the Interpretation of Genomes) system (http://genomeprojectsolutions. com/ PHRINGE_pipeline. html) by eliminating any transcripts shorter than 300 nucleotides and retaining only the longest version of any splice variant at each locus (Supplementary Note).
Estimation of novel genes In order to identify novel genes, we first reduced the redundancy of the platyfish transcriptome by clustering similar (>95% identity) sequences. Sequences from clusters with no identifiable members were filtered to remove sequences that mapped (by GMAP  51  ) with less than 99% identity to the genome or had predicted coding sequences shorter than 300bp. Finally, identities for the remaining sequences were sought in the non-redundant database (NCBI). A separate clustering by genomic distance (1kb) produced a very similar gene number estimate. (Supplementary note).
Annotation of non-coding RNAs To detect snoRNA, snRNA, miRNA and rRNA a homology-based prediction was done using the multispecies RNA database (http://www. ensembl. org/info/data/ftp/index. html) and combined with zebrafish, stickleback, medaka and Takifugu ncRNA libraries. tRNAs were annotated using tRNAscan-SE. 21 software locally on UNIX  52. rRNA, miRNA, snRNA and snoRNA were predicted by BLASTN using other fish ncRNA database as query and duplicates were removed from the output files (Supplementary Tables  11 12 ). Fish databases were downloaded from Ensembl on the following genome versions: zv9 (Danio rerio), BROADS1 (Gasterosteus aculeatus), HdrR (Oryzias latipes) and FUGU4. 0 (Takifugu rubripes). miRNA sequences were identified with the Vienna RNA package of MiRscan(http://genes. mit.
Annotation of transposable elements Both manual and automatic classification of transposable elements (TE), based on Wicker's nomenclature  53  , were performed and combined into a single library. Two TE elements were considered as different if their sequence diverged by more than 20% at the nucleotide level. Manual classification was done by searching TE sequence homology using CENSOR  54  software, by homology searching specific TE proteins using TBLATN and BLASTP, by identifying terminal repeat features (TIRs, LTRs and TSDs) using BLASTN2 and LTR_FINDER software  55  , and by reconstructing phylogeny using ClustalW alignment and maximum likelihood calculation (default aLRT) using the PhyML package  38. Phylogenetic reconstructions for the DNA, LINE and LTR classes (Supplementary Fig. 1 2 3 ) were based either on transposase or reverse transcriptase proteins.
Analyses of viviparity genes Thirty-four protein-coding genes known to function in yolk production, placenta-related characteristics, and zona pellucida structures were selected as candidate genes (Supplementary Notes) for the evolution of viviparity among Xiphophorus fishes. Eighteen randomly selected genes were used for control. Orthologous sequences for these genes from four fish species (O. latipes, G. aculeatus, T. nigroviridis, D. rerio) were retrieved from the Ensembl database and then aligned using the MAFFT translation alignment. PAML (version 4. 4, linux 64bit) was implemented to test if genes are under positive selection using branchsite specific model  58. Genes with p-value less than 0. 05 from likelihood ratio tests were designated as positively selected in Xiphophorus and the Bayes empirical Bayes method  59  was further used to calculate the selection pressure at each site.
Analysis of post-TGD gene retention Cognition, pigmentation, and liver gene orthologs of human, mouse, and teleosts were obtained from Ensembl65 and missing gene annotations identified with TBLASTN (Supplementary Notes, Supplementary Table  7 ). EnsemblCompara GeneTrees were checked for teleost duplications and TGD-based duplications were confirmed using the Synteny Database  10. Xiphophorus orthologs were identified from transcriptome v4 and the genome using BLAST searches and assignment confirmed with the Synteny Database. Potential bias in TGD duplicated retention for dosage sensitivity, protein complex membership, and gene length was tested (Supplementary Notes). (A) Female (upper) and male (lower) platyfish, Xiphophorus maculatus of strain Jp163A with black pigment spots in the dorsal fin that develop when activity of a X-chromosomal oncogene is appropriately controlled.
In hybrid this control is compromised and malignant melanoma develop from the spots. (B) Phylogenetic position of the platyfish relative to other species mentioned herein. Phylogenetic tree of endogenous retroviruses based on reverse transcriptase protein sequences. Note that the endogenous foamy virus sequences form two distinct tetrapod-and fish-specific phylogenetic groups. Alignment was made with clustalW (223 amino acids) and the phylogenetic tree was constructed with the PhyML package using maximum likelihood methods  38    Conserved syntenies between platyfish and medaka. (A). The medaka orthologs of genes on X. maculatus chromosome 9 (Xma9) tend to lie on O. latipes chromosome 4 (Ola4), showing that the genic content of these chromosomes has remained intact with no translocations in the 120 million years since the lineages of these species diverged.
Acknowledgements The authors would like to thank the staff of the  Xiphophorus Genetic Stock Center  and the  Biocenter Fish Facility  for maintaining the pedigreed fish lines used in this study. We gratefully acknowledge sequencing efforts of  Catrina Fronick ,  Kim Delehaunty , and the production sequencing group at the  Genome Institute. This work was supported by  National Institutes of Health, NCRR and ORIP, Division of Comparative Medicine  grants  R24 RR024790  and  R24 OD011120  (RBW) including an American Recovery and Reinvestment Act supplement to this award, and  R24OD011199  (RBW),  R24 RR032658-01  (WCW),  R01 RR020833  and  R01 OD011116  (JHP), by the  Deutsche Forschungsgemeinschaft, TR 17 (MS) , and the  Agence Nationale de Recherche (JNV).
package www. geneious. com/; Transcriptome http://avogadro. tr. txstate. edu/cgibin/gb2/gbrowse/XM_ncbi442/ http:// http://xiphophorus. genomeprojectsolutionsdatabases. com/ http://avogadro. tr. txstate. Platyfish Genome at Ensembl http:// www. ensembl. org/Xiphophorus_maculatus/Info/Index; GenBank Assembly ID GCA_000241075. 1; http://www. ncbi. nlm. nih. gov/ genome/assembly/?term=GCA_000241075. 1; Genomic variants database http://dgvbeta. tcag. ca/dgv/app/home; Human Protein Reference Database www. hprd. org Accession codes All sequence data have been deposited in the NCBI database with accession numbers AGAJ00000000.