dataesr/scientific-paragraphs-categorization huggingface dataset:
Second, with the continuous mixed cell centers and various weights, we build the MSS in the next time frame by translation and scaling from the current frame. Third, we apply the GMSSTF to partial molecular movements, which is potentially useful in mimicking a single molecule movements. Last, we apply our algorithm to both CPU and GPU approaches of MSS construction to show the efficiency improvements. All experiments are performed with molecular structure downloaded from the public protein database PDB (Protein Data Bank http://www. rcsb. org/pdb/). In summary, the MSSTF has the following four contributions to the literature: (1) Modeling Dynamic Animation Process. It is the first computational framework which requires no reconstruction for the intermediate MSSs using unions of balls. Both the underlying mixed cells structure and the MSS are moving continuously with formulated mathematical expressions.
Results We apply the GMSSTF to both CPU and GPU approaches of MSS modeling. Suppose the source molecule consists of m atoms and the target molecule consists of n atoms. In the process of transformation, both CPU and GPU approaches reconstruct each intermediate MSS using m × n balls. It is noted that both approaches construct the underlying Voronoi and Delaunay complexes and mixed cells on CPU in the first phase (Figure  4 ). In contrast, the GMSSTF precomputes the fixed underlying Voronoi complex and transforms the Delaunay complex and mixed cells using linear interpolation. The new approach largely saves the time in the MSS transformation process. Nine closely related molecule structures are downloaded from the Protein Data Bank (http://www. rcsb. org/pdb/) [4]  to form ten different transformation processes.
The PDB IDs of the nine molecules are 1J5F, 100D, 133D, 101D, 1AIE, 1D63, 114D, 161D, and 1XD7. All downloaded files are followed with extension *. pdb. In Table  4 , we compare the CPU construction time with/without GMSSTF using Kruithof and Vegter's approach (KVA)  [26]  and Cheng and Shi's quality mesh approach (CSA)  [28]. The experiment is performed on a machine with Intel i5@2. 7 GHz and 8 GB RAM. Each transformation process generates 1000 intermediate MSSs. The average time taken for each intermediate MSS with the source and target molecules and the number of atoms is listed in Table  4. Figures  10  and 11  show the computational time differences using KVA and CSA with/without GMSSTF, respectively. It is clear that the GMSSTF largely reduces the computational time on generating intermediate MSS in the transformation process because of the reuse of intermediate Delaunay and Voronoi complexes.
Conclusions and Discussions In this study, we introduced a general MSS transformation framework which is potentially useful in mimicking biological macromolecular dynamics in bioinformatics research. We illustrated the solutions for a transformation process from one molecule to another as well as the transformation of a single molecule in different forms. The proposed framework requires no anchor point or skeleton information and handles topology changes automatically. In order to validate the effectiveness of the proposed approach, we applied our method on the PDB database to model the biological macromolecular surface transformation process. The simulation results show that our method speeds up the traditional approaches. Although the traditional approaches, such as KVA, CSA, and Chavent's algorithm, also produce the similar animation process without GMSSTF, the construction of the first phase, that is, the Delaunay and Voronoi complexes and mixed cells, is recomputed for every intermediate frame.
Acknowledgments This work was supported by the  National Science Foundation of China  (nos. 61602431 ,  61572164 , and  61402417 ). This study was also supported by the foundation of talents start-up project  in China Jiliang University  (no. 000485 ), the foundation of talents start-up project  in Zhejiang Gongshang University  (no. 1120XJ2116016 ),  Zhejiang Provincial Natural Science Foundation  under Grant no. LY15F020037 , and  Key University Construction Projects of Hangzhou Dianzi University  under Grant no. GK168800299017-9.
Detectors with intensity from Bragg reflections, characteristic of crystalline samples, were eliminated using the program LAMP available at the ILL  (Richard et al. , 1996)  so that mostly the incoherent contributions in the spectra could be analyzed. The observed quantity in IINS experiments, the scattering function ( , ), where Q is the modulus of the scattering wave vector and ω is the energy exchange between the sample and the neutrons, contains different molecular contributions and distinguishes different types of motion depending on the temperature and energy resolution (time) range of the spectrometer. We note that the behavior of ( , ) mainly reflects the motions of hydrogen atoms, as they possess a much larger incoherent scattering cross section than that of any other atom in these systems.
(iii) The inelastic scattering, ( , > 0) , gives information on the external (intermolecular) as well as internal (intramolecular) molecular vibrations in the system. This type of information is complementary to what can be obtained by IR and RS spectroscopies. The measured ( , > 0) can be transformed into the so-called generalized density of states (GDOS) as a function of temperature within the incoherent one-phonon approximation using the software LAMP  (Richard et al. , 1996)  to derive details of the molecular vibrational modes  (Squires, 2012 ) ( ) = ∑ ( , ) = ℏ exp - ℏ ( , ) (4) ( , ) is the experimental incoherent scattering function dominated by the Hmotions. ( , ) is obtained by averaging over the scattering angles considered in the experiment in order to improve the counting statistics, which implies that coherence effects in the scattering are also averaged.
Acknowledgements Work by MLM was financed by the  Science without Borders Program  (grant number  205609/2014-7 ) and HJ partially funded by an internship grant offered by the  Institute Lauevon-Langevin  (ILL). ECS work was financed by the  Norwegian Research Council  ( RCN) SYNKØYT Program  (project number  228551 ). The work of RI was part of a student project and supported by collaboration between HNB and AM. EP acknowledges  FAPESP  (#  14/1447-5 ) grant. We acknowledge the support of the ILL in providing the neutron research facilities used in this work. This was financed by  NMI3 , CoNext and Danscatt. The thermoanalysis apparatus used in the work were financed by Carlsbergfondets (grants  2013_01_0589  and  CF14-0230 ). This research also used resources of the  National Energy Research Scientific Computing Center , a  DOE Office of Science User Facility  supported by the  Office of Science of the U.
Acknowledgements We are grateful to  Professors Pere Alemany  and  Josep Maria Boll  and  Dr Miquel Huix-Rotllant  for valuable insights and fruitful discussions. This study has been supported by the  Basque Government  (project  IT588-13 ) and the  Spanish Government MINECO/FEDER  (projects  CTQ2016-80955  and  CTQ2015-64579-C3-3-P ). D. C. thanks  IKERBASQUE, Basque Foundation for Science for nancial support. C. C. is indebted to the  Spanish "Ministerio de Economía y Competitividad" for a pre-doctoral FPI  grant and an  EEBB mobility grant  for a research stay in Marseille. M. B. thanks the support of the A*MIDEX grant (No. ANR-11-IDEX-0001-02 ) and of the project  Equip@Meso  ( ANR-10-EQPX-29-01 ), both funded by the  French Government "Investissements d'Avenir" program. C. J. B. acknowledges support from the  National Science Foundation , grant  DMR1508099.
Structure determination The unit cell parameters, optimized by least-squares refinement were calculated and refined using indexation of collected intensities. The total number of measured reflections was 4599 among which 2748 were independent and 2439 had intensity I > 2r(I). The selenic atoms were located using the direct methods with program SHELXS-97  [15]. The oxygen and the organic moieties were found from successive Fourier calculations using SHELXL-97  [16]. The water H atoms were located in a difference map and refined with O-H distance restraints of 0. 88(2) A ˚and H-H restraints of 1. 5(2) A ˚so that the H-O-H angle would fit to the ideal value of a tetrahedral angle. Next, the hydrogen atoms of the C(N)H and NH 2 groups were fixed geometrically by the appropriate instructions of the SHELXL-97 program (HFIX 43, HFIX33, and HFIX 93, respectively)  [15].
All the compounds were identified by spectral analysis, mainly ESI-HRMS, UV and NMR experiments ( 1 H, 13 C, DEPT, DOSY, COSY, NOESY, HSQC and HMBC) and comparison of their spectroscopic data with those reported in the literature. Compounds 5, 7, 8, 9, 10 and 14 were new for the genus Helianthemum. The investigated extracts and isolated compounds were evaluated for their free radical scavenging capacity by on-line HPLC-ABTS •+ screening. The antioxidant properties were confirmed by ORAC and TEAC assays. The results clearly indicated high antioxidant potential of the extracts and tested compounds of this species and agreed with literature data that free radical scavenging activity depends on the molecular structure, the number and position of the hydroxyl groups of tested compounds. Moreover, given the large amounts isolated and purified in this work, of trans-tiliroside and rutin which besides its numerous recognized biological activities, is used as oral complement; it becomes important to note that this Helianthemum species might be developed industrially for its rich content of these bioactive components.
Intermolecular interactions control the crystal packing of organic molecules. As a consequence, the accurate calculation of lattice energies in the later stages of crystal-structure predictions is crucial. Price (2004)  has for instance developed nonempirical anisotropic polarizability-based atom-atom potentials for use in crystal-structure prediction studies. Statistical rules concerning atom-atom contacts in crystals is experimental database derived knowledge which contributes towards a better understanding of crystal packing formation. The forces acting between molecules/functional groups are of electrostatic and van der Waals nature, while interactions are also classified as hydrophobic versus hydrophilic. There is a large amount of literature investigating the role of O atoms in crystal interactions and crystal engineering.
According to  Gilli et al. (2009)  weak hydrogen bonds are basically electrostatic, while stronger ones are mixtures of electrostatic and covalent contributions. The involvement of functional groups in crystal packing contacts is widely investigated in the literature in order to better understand the principles of crystal formation. Galek et al. (2010)  have for instance developed the Logit hydrogenbonding propensity method to accurately predict which hydrogen bonds might form in an organic crystal structure. Hydrogen-bond propensity models were constructed using crystal structures archived in the Cambridge Structural Database (CSD;  Allen, 2002)  Analysis of intermolecular interactions using the Hirshfeld surface-based tools represents a major and popular tool which enables strong contacts in crystals to be highlighted  (Spackman & McKinnon, 2002).
Fingerprint plots can be made with the software CrystalExplorer  (McKinnon et al. , 2004)  by evaluating the pairs of d i and d e distances from the Hirshfeld surface to the nearest atom interior/exterior to the surface, respectively. Later the d norm quantity was introduced by  McKinnon et al. (2007)  to identify short contacts, i. e. those which are shorter than the sum of van der Waals radii of the two atoms interacting. Molecular shape is important in both crystallization and supramolecular assembly and its description using spherical harmonics can be used to classify molecules and their crystal packing  (Spackman et al. , 2016). This Hirshfeld surface analysis can be used in combination with the computation of the different contact enrichment ratios, described by  Jelsch et al. (2014 Jelsch et al.
, 2004). The computation of the Hirshfeld surface and of enrichment ratios calculation were carried out with the software MoProViewer  (Guillot et al. , 2014)  and an example is illustrated in Fig. 1. The software computes at first two three-dimensional grids containing the electron densities M and C generated respectively by the reference molecule and by its environment. A fast calculation of the spherical atom electron density is proposed although a multipolar atom modelling is also possible. Then, a three-dimensional grid containing the values W = M /( M + C ) is generated and the Hirshfeld surface can be displayed by choosing an iso-contour level of 1 2. The positions of the H atoms were adjusted according to the average bond distances derived from neutron diffraction experiments  (Allen et al.
Selection of molecules The crystal structures for several families of oxygenated hydrocarbon molecules were retrieved from the Cambridge Structural Database (CSD;  Allen, 2002)  searches. The families of structures were retrieved from the CSD using combinations of criteria, such as notably the chemical species present and the presence of the desired oxygen chemical function(s). To limit the number of entries retrieved, the absence of some other frequent oxygen chemical functions was also required. An example of protocol to search molecules in the CSD is given in the supporting information for the chloro-ether compounds. Molecules with H atoms missing or with disorder were not retained. In general, only structures with a single molecule in the asymmetric unit and no solvent were kept. A number of molecules with a hydroxyl substituent were discarded as the crystal structure showed a wrong orientation of the H atom, leading to short O-HÁ Á ÁH-O contacts.
This result suggests that, in an environment devoid of hydrophilic H atoms, the nitro O atoms exhibit a slightly more pronounced hydrogen-bond acceptor character than the ether oxygen. The presence of two close O atoms presumably generates a slightly more electronegative potential around a nitro group compared with the ester O atom which makes it more attractive to very weakly charged H-C atoms. The donor and acceptor strengths based on mean distances in C-HÁ Á ÁO hydrogen bonds were quantified by  Steiner (1998)  in a crystallographic database study; the nitro and ether groups were included in the investigation. The HcÁ Á ÁO distances were not systematically shorter for one of the two moieties, rather the relative distances were strongly dependent on the nature of the C-H donor. For strong donors such as water or NH 3 + , the nitro group was ranked as a weaker acceptor than the ether.
Conclusion The interactions formed by several oxygenated chemical functions in crystal structures retrieved from the Cambridge Structural database have been compared. The Hirshfeld surface permits analyzing intermolecular interactions while maintaining a whole molecule approach. The contact enrichment methodology on families of compounds is a valuable tool to compare the likelihood of different contacts to occur. The analysis of contacts between chemical species which are subdivided in sub-groups yields indications on the relative strengths of the different interactions. The current study focuses on the interactions of several chemical types of O atoms and notably on their propensity to form weak and strong hydrogen bonds. For instance, in the ester hydrocarbon compounds, there are two types of O atoms.
The more systematic application of crystal structure validation software such as checkCIF  (Spek, 2003)  would be of great benefit to identify such errors, notably for crystal structures published in chemistry journals. The article gives a few examples of multiple linear regressions which are directions to further explore in future investigations of crystal packing contacts in conjunction with Hirshfeld surface tools. Many descriptors such as the size/ shape of the molecule, electrostatic moments, molecular symmetry, geometric distribution of chemical groups etc. could be incorporated into the modeling, in addition, to the chemical proportions of the molecule. The E value cannot always be considered as a statistic as it results sometimes from a single observation, in the case of molecules where there is only one copy of a chemical type.
Acknowledgement The authors thank the  Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)  ( PIP-0352 ), the  Agencia Nacional Científica y Tecnológica  ( PICT11-0647  and  PICT14-3266 ), the  Facultad de Ciencias Exactas, Universidad Nacional de La Plata  ( UNLP-11/X684 ) and the international cooperation program ECOS-MinCyT ( A13E05 ) for financial support.
This analysis showed the high sensitivity and specificity of our strategy, relatively independent of the reference proteome. The workflow increased the length of proteins products in A. thaliana by 13%, allowing, often, to recover 100% of the protein sequence length. In addition redundancy was reduced by a factor greater than 3. In coconut, the approach generated 29,366 proteins, 1,246 of these proteins deriving from new contigs obtained with the BRANCH software. The coconut proteome presented a functional profile similar to that observed in rice and an important number of metabolic pathways related to secondary metabolism. The new sequences found with BRANCH software were enriched in functions related to biotic stress. Our strategy can be used as a complementary step to de novo transcriptome assembly to get a representative proteome of a target species.
Genetic and genomic knowledge in this species is still minimal; to date NCBI database reports only 1,008 ESTs sequences and 3,903 proteins  [3]  and several transcriptomes  [4] [5] [6]. On the contrary, oil palm (Elaeis guineensis L. ) receives greater attention because of its high productivity and profitability, which made palm oil the most common oil on the world market  [7]. The interest in oil palm led to the sequencing of the genome of a palm species for the first time  [7]. Genomic resources have also been developed for other palms such as the date palm  [8]  offering the opportunity to resolve fundamental questions of palms biology and opening new routes to the genetic improvement of these species  [8] [9]. For example, was the whole genome duplication experienced by Elaeis guineensis  [10]  shared by coconut and did it affect gene families diversification?.
These factors prevent obtaining a correct proteome that can be used in downstream analysis. A recent study showed that Trinity, a software dedicated to de novo assembly, has a high resilience to chimerism, while this software and some others with high performance (CLCscaf-S, SOAPtrans-S) have a significant rate of fragmentation as a result of the difficulty of assembling coding sequences with either low or high levels of expression  [14]. Some studies have explored translational genomics to improve de novo transcriptome in non-model organisms. In order to identify the allelic variation present in the transcriptome of 14 different genotypes of Lolium perenne, a methodology based on orthology was developed  [15]. This strategy called Orthology Guided Assembly (OGA) identifies the transcripts that can be orthologous to genes of a group of reference species and reduces redundancy by using CAP3 software.
Another approach with CAP3 software is the scaffolding translation mapping (STM) method that maps reads and transcripts to the proteome of a reference species  [16]. CAP3 is considered to be a conservative tool, demanding a high similarity between sequences  [17]. This feature can prevent this tool to capture all the redundancy in de novo contigs or perform the scaffolding when the degree of overlap between the fragments is not long enough to be identified by this program. Thus CAP3 may not be completely adequate to reduce contig redundancy and their scaffolding. In order to overcome these hindrances, we developed a methodology that reduces the fragmentation and redundancy of de novo transcriptomes by providing a workflow to build a reference proteome in a neglected species (coconut). The main characteristics of this workflow are: i) Identify new contig sequences with BRANCH software  [18] , aligning reads and de novo transcriptome to a closely related well-studied organism (oil palm).
ii) Translate a large pool of polypeptide sequences from transcriptome with FrameDP software  [19]. iii) Process the alignments of these polypeptides to an oil palm proteome (Fig  1 ). We validated our methodology by reversing the logic of model species and reassembling a well-known proteome from RNA-Seq data. Arabidopsis thaliana is a model species and has been the first plant genome to be sequenced  [20]. Genomic resources are also available on related species such as Arabidopsis lyrata and Capsella rubella  [21, 22]. These species have diverged around 12 and 23 M. Y. A respectively from Arabidopsis thaliana  [23]. In order to evaluate the performance of our methodology and the influence of the reference species on the results, we assembled the Arabidopsis thaliana proteome from transcriptomic data, using Capsella rubella and Arabidopsis lyrata proteomes as references.
Workflow used to improve a target transcriptome by using a reference genome Our methodology, starting from short nucleotide sequence reads generated by New Generation Sequencing technologies (NGS) of a transcriptome, involves five steps summarized in Fig 1A. Step 1. de novo assembly of a target transcriptome. NGS transcriptomic studies are generally represented by paired-end reads. The target paired-end reads were trimmed using Trimmomatic V033  [24]. Transcriptomes were assembled with the software Trinity  [25]. We used the BRANCH software as a first strategy to improve de novo transcriptome by translational genomics. BRANCH can identify novel contigs, extend incomplete contigs and join fragmented ones by using partial or related genomic sequences  [18]. In the current analysis we used BRANCH with default parameters to find new contigs by using the reads and target contigs assembled at step 1 and the mRNA of the reference species as a related genomic sequence.
Step 2. Contigs translation into polypeptide sequences. The target transcriptomes and the new sequences found by BRANCH software were pooled. Identical sequences (full-length and fragments) were removed with cd-hit-est V4. 6. 4 software  [26] , retaining the longest sequence as the representative of the redundant group. These transcripts were translated into polypeptide sequences with FrameDP V1. 2. 2 software  [19]  and default parameters, using Uni-ProtKB viridiplantae proteins  [27]  and relevant reference databases [28-30]. Step 3. Alignment of polypeptides to reference proteins. The target polypeptides of the previous step were aligned to the proteins of the reference species using BLASTP  [31]. The alignments were processed to recover high-scoring segment pair (HSP) which do not overlap over more than 1 amino acids (aa).
Otherwise, the target polypeptides were joined with n times"X" where n represents the distance between the alignments of these polypeptides. Steps 4 and 5 and the identification of potential chimeric sequences were executed by a series of scripts that can be obtained at http://palm-comparomics-pj. southgreen. fr/Download. html/Scaff. RRed. tar. gz. A more detailed explanation of the use of this script is found in S1 File.