dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank  D. Reinberg  for the generous gift of SSRP1 antibodies. We also thank  A. G. Ladurner  for providing a plasmid encoding the human Spt16 cDNA. We greatly acknowledge the  PICT-IBi-SA@Pasteur Imaging Facility of the Institut Curie , member of the France-BioImaging national research infrastructure. L. P. was supported by the  European Commission   FP7 Marie Curie Intra European Fellowship "CenHFD. "This work was supported by  La Ligue Nationale Contre le Cancer (Equipe labellisée Ligue) , the  European Commission Network of Excellence EpiGeneSys  ( HEALTH-F4-2010-257082 ),  ERC  Advanced Grant  2009-AdG_ 20090506  "Eccentric," the  European Commission Large-Scale Integrating Project  ( FP7_HEALTH-2010-259743  " MODHEP" ),  ANR-11-LABX-0044_DEEP ,  ANR-10-IDEX-0001-02   PSL, ANR " CHAPINHIB "  ANR-12-BSV5-0022-02 ,  ANR  " Epicure "  ANR-14-CE16-0009 ,  ANR  " CELLECTCHIP ,"  ANR-14-CE10-0013 , and Aviesan-ITMO cancer project " Epigenomics of breast cancer.
"D. J. P. acknowledges support by the  STARR Foundation , the  Leukemia and Lymphoma Foundation , and the  Memorial Sloan-Kettering Cancer Center   Support Grant/Core Grant  ( P30 CA008748 ). K. F. S. acknowledges support of the  Science Foundation Ireland  under grant numbers  05/RP1/B793  and  12/IA/1370. The Institut Curie Mass Spectrometry platform acknowledges support from  Région Ile-de-France  ( 2013-2-EML-02-ICR-1  and  2014-2-INV-04-ICR-1 ) and  Fondation pour la Recherche Médicale  ( DGE 20121125630 ) grants to D. L.
Code availability We used NEMO 3. 6 svn 7036, which can be downloaded through this command: $ svn checkout -r 7036 \ http://forge. ipsl. jussieu. fr/nemo/svn/ branches/2015/nemo_v3_6_STABLE However, the latest stable version of NEMO is usually advisable. A login will be asked that you can create on the NEMO website. The manganese module comes as part of different Fortran 90/95 source code files that are to be found in the electronic supplement. Those should be put in NEMOGCM/CONFIG/ * /MY_SRC/ that adds and overrides symlinks in NEMOGCM/CONFIG/ * /WORK/. The asterisk must be replaced with your configuration name that should be based on ORCA2_OFF_PISCES. Both NEMO and the manganese model are available under the CeCILL licence. Model output data are available at https://doi. org/10. 1594/ PANGAEA.
DdPCR-Tail is comparable to qPCR and fluorometry (QuBit) and allows sensitive quantification by analysis of barcode repartition after sequencing of multiplexed samples. This study provides a direct comparison between quantification methods throughout a complete sequencing experiment and provides the impetus to use ddPCR-based quantification for improvement of NGS quality. Next Generation Sequencing (NGS, also called High Throughput Sequencing) has facilitated a surge of new discoveries, from genotyping cohorts of patients for the identification of disease-associated mutations to the exploration of cellular processes and chromatin landscapes 1-3. Whole-genome sequencing 4-8 has become the method of choice for acquiring large data sets for broad genomic analyses, including the International Network of Cancer Genome Projects 9 , Cancer Genome Atlas Research Network 10 , the Integrated Genomic Analyses of Ovarian Carcinoma 11 , and the Encyclopedia of DNA elements project (ENCODE)  12.
Next, using our indexed approach, we evaluated the reproducibility of titration methods regardless of the indexing sequence, since all libraries are identical (from the exact same preparation) and represent technical replicates. Ideally, a reliable and sensitive technique will allow the indexing of multiple samples in a homogenous fashion (equal ratios). Optimal balancing of the indexed libraries would result in a ~16% per indexed library (approximately one sixth of 100%). QuBit and ddPCR-Tail provided the most stable results (Fig. 3c ), with the least amount of variability between measures relative to a lower variation between DNA indexed libraries (reported by lower standard deviation respectively ddPCR-Tail SD ± 3. 1; QuBit SD ± 1. 9; qPCR SD ± 7. 2 and ddPCR SD ± 8. 9). However, when representing the data to appreciate the true repartition between index sequences (Fig.
NGS sequencing analysis. After titration, 12 pM of DNA was loaded into the flow-cell. PE-Sequencing was done in a HiSeq2500 with a read length of 100nt. The resulting sequencing data was then treated, sorted and quality controlled using FastQC Programs (Babraham Bioinformatics; Andrews S 2010. FastQC High Throughput Sequence QC Report)  27. We report here the quality score, the total number of reads, and the individual number of reads per index for each of the titration methods. The full NGS data from the sequencing is available through NCBI SRA database under the accessing number NCBI SRA PRJNA260389.
Acknowledgements We would like to thank the  UT Southwestern McDermott Center  for their assistance in library sequencing and quality analysis. We would also like to thank  BioRad  for material support. The lab is supported by the  National Cancer Institute (Lung SPORE   P50CA70907 );  RO1 AG001228 , and a distinguished chair from the  Southland Financial Foundation in Geriatrics Research  (jws and wew). This work was performed in laboratories constructed with support from  National Institute of Health  grant  C06 RR30414.
Apart from this, we also compared the total number of source and target named entities (NEs) so that they should not differ significantly which can play a major role in determining the comparability of two texts. The remainder of the paper is structured as follows. The related work on parallel data extraction and comparability measures is briefly discussed in Section 2. In Section 3, we detail our proposed method and provide the results of our experiments on WMT-2016 data in Section 4. In Section 5, we present the conclusion and directions for future work.
These translations are then used to query the database to find matching translations using IR techniques. There have been only a few studies trying to investigate the formal quantification of how similar two comparable documents are. Li and Gaussier (2010)  presented one of the first works on developing a comparability measure based on the expectation of finding translation word pairs in the corpus. Our approach follows this line of work based on a method developed by  Sennrich and Volk (2010). 3 Aligning comparable documents.
Data and systems In order to test our proposed techniques we conducted experiments on the provided development data and corresponding references. As discussed in Sections 3. 4 and 3. 5, we selected only those document pairs for comparison that have a sentence-length and word-length ratio of 1 (or very close to it). It is usually seen that on average a French translation of an English document has 1. 2 words for every English word in the original. In this work, since we are dealing with the comparable texts that are usually not proper translations of each other but contain similar information, we choose to set this ratio closer to 1. In addition to this, we applied different weighted scores for the three features (i. e. sentence-based, word-based and NE-based scoring). The weights applied on the test data were extracted from our experiments on the development data.
| Data analysis Our analyses are summarized in Fig. 2. First, diversity patterns of both pearl millet and sorghum were characterized based on named varieties on the one hand, and on SSRs markers on the other hand. Seed sources were also investigated for both species. Then, further analyses were conducted to investigate the factors involved in sorghum genetic patterns, at two levels: (i) geographic patterns of sorghum local varieties, avoiding potential confusions related to introductions of exogenous materials, and (ii) relationships between Mount Kenya genetic groups and major African clusters.
The congruence of the different runs for this K value was checked, and the run with the highest log probability was retained. For further analysis, samples whose estimated proportion of genome originating from one population (q, hereafter admixture coefficient) was below a 0. 8 threshold were considered as resulting from admixture between populations. Individuals with a q value equal or superior to 0. 8 for a given population were assigned to that population. We also used the TESS v2. 3. 1 software  (Chen, Durand, Forbes, & François, 2007)  to test whether results of this clustering algorithm converged with those of STRUCTURE. For sorghum, whose genetic diversity showed a clear geographic pattern, further analyses were conducted on local varieties (160 samples), using those plants that could be assigned to a population (q ≥ 0.
8). Isolation by distance among sites was tested with a Mantel test assessing the correlation between pairwise Nei's genetic distances  (Nei, 1972)  and log-transformed geographic distances. This test was performed with 1,000 permutations, using the mantel function of the R package ecodist  (Goslee & Urban, 2007). Then, a spatial principal component analysis (sPCA) was conducted to further detect and characterize the geographic patterns of diversity  (Jombart, Devillard, Dufour, & Pontier, 2008). A discriminant analysis of principal components (DAPC) was also carried out to test whether genetic differences existed among the local varieties collected in the ten sites  (Jombart, Devillard, & Balloux, 2010). Both analyses were performed using the spca and dapc functions implemented in the R package adegenet  (Jombart, 2008).
| Comparing sorghum genetic diversity in Mount Kenya and Africa For sorghum, we conducted a joint analysis of our data set and a subset of 1,799 individuals from the collection of African landraces studied by  Billot et al. (2013)  with 41 SSRs. STRUCTURE was first run on the subset of 1,799 individuals from the African collection for K ranging from 1 to 20 populations. The resulting groups were then used as a priori to run DAPC, based on the 14 SSRs shared with the Mount Kenya data set. Group membership of Mount Kenya varieties was then predicted using the predict. dapc function.
ACKNOWLEDGEMENTS Thanks are due to  CIRAD (Centre de Coopération Internationale en Recherche Agronomique pour le Développement)  for financing the project  ATP 06/01  in the frame of which this study was conducted, KALRO for supporting overall implementation of the project, and  Ministry of Agriculture and Government Administration  staff and farmers for their devotion and cooperation during the surveys and seed collection missions. We acknowledge the help of  Ben Kanyenji ,  former Head of Sorghum research program  at  KALRO Embu , as well as that of  Caroline Mwongera ,  Eliud Kagete , and  Peter Mucheru  for field collection and surveys,  Margaret Mwathi  at  ICRISAT  for DNA extraction, and that of the  IPS2 (Institute of Plant Sciences, Paris Saclay ) genotyping platform for pearl millet genotyping.
DNA fragments of approximately 500 bp were excised from the gel using GeneCatcher tips and purified using Qiagen Gel Extraction Kits (Qiagen, Valencia, CA). The adapter-modified DNA fragments were enriched by 12 cycles of PCR using primers PE 1. 0 and PE 2. 0. The concentration and size distribution of the library was determined with a DNA 1000 chip on the Agilent 2100 Bioanalyzer (Agilent Technologies). The library was loaded onto an indexed lane of paired-end flow cell. The reads in the flow cell were sequenced as paired-end indexed reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 1 and HiSeq data collection v. 1. 1. 37. 0 software. Base-calling was performed using Illumina's RTA v. 1. 7. 45. 0. Reads quality control was performed in Galaxy (https:// galaxyproject.
Protein-coding sequence prediction, annotation, and validation Protein-coding sequences were predicted using GeneMark_ES v. 2. 3c  [34] , which employs an intrinsic method with unsupervised training based on an ab initio algorithm. The algorithm features an enhanced intron sub-model to accommodate sequences with and without branch point sites found in several fungi (Ascomycota, Basidiomycota, and Zygomycota). Proteins were annotated against NCBI non-redundant (NCBI_nr) (http://www/ncbi. nlm. nih. gov) and HMMER (http://hmmer. janelia. org) databases. The latter was also used to identify protein profiles (Pfam). For overall analyses with blastp an e-value cut off of 1E-5 was used, except for detecting candidate effectors where a higher e-value cut off was permitted (1E-2). Proteins with a signal peptide or anchor peptide were predicted by SignalP 4.
1  [35]. Small secreted proteins (SSPs) were considered those of less than 200 aa without transmembrane domains. Cysteinerich SSPs in the CmTG12bL2 genome were identified as previously described  [28]. HCSSPs were resolved as in  [28]  with at least twice the average of cysteines in the CmTG12bL2 proteome and as in  [24]  as those SSPs containing more than 2% cysteines. The CmTG12bL2 predicted genes were validated using three strategies. First, the protein set was compared to a core of 458 highly conserved proteins  [36]. This core consisted of highly homologous proteins that are present in six eukaryote genomes (Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, and Schizosaccharomyces pombe), and was selected from the KOG (clusters of euKaryotic Orthologous Groups) database.
Identifying carbohydrate-active enzymes (CAZymes) For the detection of encoded CAZymes, each CmTG12bL2 protein model was compared (blastp) to proteins listed in the Carbohydrate-Active Enzymes database (www. cazy. org) [38]. Model CmTG12bL2 proteins with a length of over 50% identity to those in CAZy database were directly assigned to the same family (or subfamily when relevant). Proteins with less than 50% identity to a protein in CAZy were all manually inspected for conserved features such as the catalytic residues. Sequence alignments with isolated functional domains were performed in the case of multimodular CAZymes  [39]. The same methods were used for all fungi that were compared to CmTG12bL2 proteins. Putative roles of the enzymes were inferred from annotations of proteins returned from searches against the profile-HMMER database (hmmscan) and protein sequences database (phmmer) using an e-value cut off of 1E-33.
Nonribosomal peptide synthetase and polyketide synthase identification and phylogenetic analysis NRPSs and PKSs were identified by comparing the CmTG12bL2 proteins to the well-curated dataset of C. heterostrophus (Ch_NPSs)  [40, 41]  using an in-house script and to other NRPSs and PKSs from NCBI_nr (blastp, 1E-5). Additional motifs in proteins with AMP domains and ketoacyl synthase (KS) domains were identified using HMMER hmmscan (with default settings unless otherwise specified). A degenerate AMP domain in the predicted CmTG12bL2 protein CM_1661, homologous with Ch_NPS6 was identified through manual inspection  [42]. AMP domains of CM_3163 were compared to the corresponding C. heterostrophus homologous domains NPS1, NPS3, and NPS13. Finally, putative NRPSs and PKSs from CmTG12bL2 were blasted to proteins of C.
miyabeanus WK-1C. A phylogenetic analysis with the CmTG12bL2 AMP domains was done using methods described by Bushley and Turgeon  [40]  to compare conservation and relationships of AMP domains with those identified in the reference species C. heterostrophus C5, C. heterostrophus C4, and the rice isolate C. miyabeanus WK-1C  [24]. Several AMP domains from NRPSs in other Ascomycetes species that encode known chemical products were included as well. Acyl-adenylating enzymes (acyl-CoA-synthetases, CPS1, long chain fatty acids, acyl-CoA-ligases, and ochratoxins) from C. heterostrophus and other ascomycetes were used as outgroups. Protein sequences were aligned using MAFFT and a maximum likelihood phylogenetic tree was constructed in RAxML using the best protein model determined by ProTest (RT-REV-F) as in  [24, 40].
Predicted transporter and detoxification systems P450 monooxygenases were obtained by comparing the CmTG12bL2 protein set (blastp, evalue cut off 1E-5) to the Fungal Cytochrome P450 Database (FCPD; http://p450. riceblast. snu. ac. kr/download. php). The MFS and ABC transporters were predicted by comparison to the transporter classification database (www. tcdb. org) with an e-value cut off of 1E-05.
Only reads with an average Q score 30 were aligned onto the CmTG12bL2 draft genome for transcriptome assembly using TopHat v1. 4. 1  [44]  implemented in Galaxy. The CuffLinks suite of tools  [45]  was used for transcript assembly and quantification. Transcript abundance was estimated using RPKM (Reads Per Kilobase of transcript per Million mapped reads)  [46]. RPKM values were log 2 transformed and data distribution was visualized using JMPin (SAS Institute Inc. , Cary, NC, USA). Experimental variability of the log 2 of RPKM between biological replicates was estimated using Pearson's correlation coefficient for the 9,960 transcripts that were present in all replicates. For subsequent data analysis only transcripts found in at least three of four replicates were used. Transcripts were functionally categorized using Blast2GO (www.
blast2go. com) against the NCBI non-redundant (NCBI_nr) and Swis-sProt/InterPro databases. An enrichment analysis was performed with the 10% most abundant transcripts using a Fisher exact test with a false discovery rate (FDR) of 0. 05 implemented within Blast2GO  [47]  to identify overrepresented or enriched GO terms using the whole set of transcripts as reference.
Quantitative RT-PCR (qRT-PCR) experiments qRT-PCR experiments were done to validate expression of the transcriptome analysis at 48 hai and to compare the expression levels to an additional time point at 24 hai in planta and to the fungus grown in vitro. cDNA synthesis for all the treatments was carried out with the iScript cDNA synthesis kit (Bio-Rad Laboratories Inc. , Hercules, CA). CmTG12bL2 specific primers for the selected genes Ecp6 (Cm_2799), CYP53 (Cm_8068), salicylate hydroxylase (Cm_9653), β-1,4-endoglucanase (Cm_1858), β-1,4-endoxylanase (Cm_8238), and β-1,4-glucosidase (Cm_28)) were designed using the SciTools software at IDT (http://www. idtdna. com/scitools/ Applications/RealTimePCR). The genes expression levels in planta were compared to those of the fungus grown in vitro (reference sample).
qRT-PCR reactions were done in 96-wells plates using an Applied Biosystems 7500/7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA). Each reaction of 20 μL contained 10 μL iTAQ™ Universal SYBR Green Supermix (Bio-Rad Laboratories Inc. ), 0. 1 μL of each primer diluted to 0. 1μM, 3 μL of cDNA template and 6. 8 μL of nuclease-free water. PCR condition were 95°C for 2 min, 40 cycles of 95°C for 3 s, 60°C for 30 s, and 95°C for 15 s, followed by 60°C for 1 min, 95°C for 15 s, 60°C for 15 s (melt curve generation). The delta-delta Ct method was computed by the Applied Biosystems software and used for relative quantification of gene expression. Expression data were normalized against an endogenous control (glyceraldehyde-3-phosphate dehydrogenase gene). Two to three biological replications with at least two technical replicates were analyzed per gene.
C. miyabeanus fungal genome assembly, gene prediction, and validation Read statistics and quality are summarized in S1   1 ) and contained 2,378 scaffolds with a N 50 value of 74,921 bp. This Whole Genome Shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession LNFW00000000. The version described in this paper is version LNFW01000000. The total number of protein-coding sequences initially predicted by GeneMark-ES was 12,142. After discarding partial genes  (1, 142) , due to the presence of internal stop codons or lack of either initiation or stop codons, 11,000 coding sequences remained for further analyses. The average C+G content was 52. 63% for predicted genes, 52. 74% for exons, and 45. 69% for introns, versus 50. 5% for the entire genome. Additional genome assembly features are shown in Table  1.
Interrogation (blastp, 1E-05) of the 11,000 predicted proteins with the NCBI_nr database resulted in 10,395 matches (94. 5%), of which 92. 3% were annotated as hypothetical proteins, mostly belonging to other Cochliobolus species (92. 2%). A total of 7,567 motifs were identified when comparing (blastp, 1E-05) all predicted proteins to collections of protein profiles (http://hmmer. janelia. org/). CmTG12bL2 gene models were also validated (blastp, 1E-05) against a core dataset of 458 highly conserved eukaryote proteins  [36]. All but two of the 458 core proteins had at least one predicted CmTG12bL2 homolog (S2 Table ). Of the two core proteins that could not be directly identified: KOG1291 (Mn 2+ and Fe 2+ transporters of the NRAMP family) and KOG2749 (mRNA cleavage and polyadenylation factor IA/II complex), the latter matched a partial protein.
Additionally, two CmTG12bL2 proteins, CM_8436 and CM_2839, each matched two core proteins, but only one of each CmTG12bL2 protein (highest percentage of identity) is presented. Thus, 99. 1% of the core dataset could be identified in our predicted protein set. The CmTG12bL2 genome assembly was compared to the C. miyabeanus WK-1C genome (http:// genome. jgi. doe. gov). The ordered scaffolds showed good pair-wise alignment (S3 Fig) validating the assembly over relatively long distances. An additional validation was done by mapping fungal transcripts against the draft genome. Overall, 97. 6% of the predicted genes that were expressed at 48 hai in at least three biological replicates were mapped to the genome sequence.
Small secreted proteins (SSPs) The fungal secretome is essential for interactions with the surrounding environment and potential hosts. Within the SSP group are cysteine-rich secreted proteins (candidate effectors) that could interfere with plant defense mechanisms. The CmTG12bL2 proteome includes a total of 187 proteins less than 200 aa long, with signal peptides and without transmembrane domains. The number of SSP proteins is comparable to the number found in other Dothidiomycetes, although less numerous than those found in other Cochliobolus species  [28]  (S3 Table ). Most of the CmTG12bL2 SSPs (95. 7%) have similarities to hypothetical proteins from other Cochliobolus species in the NCBI_nr database including C. miyabeanus WK-1C. SSP features (S3 Table) are within or close to the range limits found in Cochliobolus species or other Dothidiomycetes  [24, 28].
More than 30 CmTG12bL2 genes had combined catalytic and non-catalytic CAZy modules. A wealth of auxiliary activities (AA) enzymes (99) was identified with diverse catalytic functions that facilitate plant lignocellulose degradation. The most prominent families were AA1, AA3, and AA9. All three subfamilies of AA1 were found containing laccases, ferroxidases, and laccase-like multicopper oxidases (LMCOs), respectively. Additional details of CmTG12bL2 CAZymes are provided in S1 Text  [77, 78, 79, 80, 81, 82, 83, 84]. To infect and obtain nutrients from wildrice tissues, C. miyabeanus needs to breach the cuticle and cell walls composed of cellulose, cross-linking glycans (hemicellulose), and pectin. Numerous CAZymes capable of degrading the backbone chains of those layers as well as removal of substitution residues for complete and efficient degradation, were predicted through electronic annotation (blastp, 1E-22) (S6 Table ).