dataesr/scientific-paragraphs-categorization huggingface dataset:
When the binding site is not known, a search on the whole protein surface--global docking or blind docking--must be performed. A classical docking program like AutoDock, designed for the small molecules docking, has been shown efficient for short peptides, such as four residues  (15)  or seven residues  (16). For longer peptides, specific approaches have been developed. Dagliyan et al. (17)  have shown the relevance of replica exchange all-atom discrete molecular dynamics simulations to identify correctly the peptidebinding sites. Verschueren et al. have proposed a protocol to generate models of a peptide at the protein surface, using backbone fragments from the BriX database  (18, 19). This method has been applied, successfully in most cases, on a dataset of 11 unbound complexes involving peptides of size up to 13 amino acids, and a dataset of 26 bound tetrapeptide-PDZ complexes.
Dataset To benchmark the performance of PEP-SiteFinder, we have used the PeptiDB dataset  (23). PeptiDB consists in 103 high-resolution peptide-protein complexes (holo conformation), resolved using X-ray diffraction, with a resolution lower than 2 Å and presenting no sequence identity between two protein monomers more than 70%. The bound peptides have a size between five and 15 amino acids. The protein uncomplexed (apo) conformation is available for 78 complexes and PeptiDB defines a core set of 41 non-redundant complexes, an additional set of 26 complexes structurally redundant with the core set according to Class-Architecture-Topology-Homologous superfamily (CATH) structural classification  (24) , and a subset of 11 complexes for which large conformational changes occur. Details about the dataset are provided in the Supplementary data.
Output PEP-SiteFinder provides several outputs. The first consists in an interactive page allowing to browse the 3D structure of the best complexes generated, to identify the protein residues close to the different peptide poses sorted according to their ATTRACT2 scores, or the protein residues having large predicted propensities to be at peptide-protein interface. This facility depends on Jmol  (32)  and thus requires a Java plug-in to be installed. The user can also download the PDB files corresponding to the protein with the interaction propensities set in the temperature factor field (columns 61-66), and to the peptide poses, organized as a multiple model PDB, together with a PyMOL script to drive the off-web analysis of the results. Finally, a file listing the propensities per residue is also returned.
Tests on the PeptiDB dataset We have assessed the performance of PEP-SiteFinder over the complete PeptiDB collection (see Supplementary data), by searching on the surface of the unbound protein conformation the experimental peptide binding site. We first focus on the results obtained for the PeptiDB core subset of 41 complexes, and we first analyze how the 10 best poses generated by PEP-SiteFinder target the actual interaction patch (summarized Figure  3A ). A major result is that the 10 best poses generated by PEP-Sitefinder fail to match any of the protein residues interacting with peptide for only four cases, i. e. for only 10% of the cases. For all other complexes, the 10 best poses generated by PEP-SiteFinder return, to different extents, relevant information about candidate residues at peptide-protein interface.
On the same data, PepSite returned results for only 29 complexes (peptide size upper limit of 10 amino acids), and could not identify any residue in the correct region for eight complexes, i. e. 27% of the cases. We also find that PepSite could identify more than 50% of the interacting residues among the 10 best poses for 48%. This highlights the added value of the PEP-SiteFinder 3D approach by comparison with a knowledge based approach such as PepSite. However, PepSite and PEP-SiteFinder both fail, for only one tar-get suggesting added value could be found in a combination of the two approaches. Interestingly as well, we found that the top three pockets identified by a pocket identification program such as fpocket do not correspond to the peptide binding site for 11 cases. For all these cases, PEP-SiteFinder returned relevant information.
Homopolymer tracts are overrepresented and overproportioned in the open reading frames of Plasmodium spp Previous analysis of homopolymer tract organisation in P. falciparum ORF reports the overrepresentation and overproportionment of all homopolymer tract types, but poly dA. dT tracts in particular  [1, 3]. To extend this analysis, ORF were obtained for all (except N. caninum) of the Apicomplexan parasites investigated here and the program Poly was used to search for and provide quantitative data for the frequency of all homopolymer tract types (Additional file 1: Table  S1 ). For comparison, a Poly analysis of human and mouse ORF were included, as these organisms represent the general eukaryotic pattern of absence of any homopolymeric tracts in these sequences  [1, 3]. Our analysis reveals that, like human and mouse ORF, the ORF of cryptosporidium, piroplasmida and coccidian parasites show no evidence of overrepresented or overproportioned homopolymeric tracts (Figure  6  and Additional file 1: Figure  S3 ).
Spatial analysis of poly dA. dT tracts in proximal flanking intergenic sequences Given the distinct overrepresentation and overproportionment of poly dA. dT tracts in the proximal intergenic sequences of three of the six Plasmodium spp. that are the aetiological agents of human malaria, these organisms were selected for an initial analysis of the spatial organisation of these homopolymer tracts using the frequency counting program motif. freq. pl (see Methods). Upstream ) reported in the respective key for that panel. Note, poly dA. dT points indicated with asterisks (T. gondii and N. caninum) were omitted from the linear regression analysis; the r 2 reported also omits these values). (2000 bases) and downstream (700 bases) sense-strand sequences for all genes were distributed into 50 base length bins for a count of the occurrence of non-overlapping poly dA.
Accounting for the differences in AT content between these three Plasmodium spp. , an "expected" frequency of occurrence of N = 5 poly dA. dT tracts can be estimated from a repeated 10× random shuffle of the sequences using the program shuffle. pl (see Methods), where the 10X shuffled frequencies are averaged to produce F 10xshuffle , ensuring that the Fraction i of all nucleotides is maintained during shuffling but not the integrity of homopolymer tracts. Plotting the normalized frequency ratio, F obs /F 10xshuffle , accounts for base composition bias and the plots show that as the Fraction i of A and T nucleotides decreases from P. falciparum to P. vivax, the ratio for these peaks actually becomes greater (Additional file 1: Figure  S4 ). That is, these spatial features of poly dA. dT tract organisation are inherent structural features and occur irrespective of AT-bias.
Methods Homopolymer tract frequency analysis using poly Annotated genome sequences for Plasmodium spp. (Plas-moDB. org release 5. 5), Theileria spp. and B. bovis (Gen-eDB. org), Cryptosporidium spp. (CryptoDB. org release 5. 5) and T. gondii and N. caninum (ToxoDB. org release 5. 1) were secured from their respective database repositories. Genbank-formatted documents were created that secured specified sizes of intergenic sequences that flank the coding sequence in each genome, taking up to the length specified unless a flanking coding sequence was encounteredin which case only intergenic sequence was secured in a truncated file. These sequence files were then concatenated into ASCII text files, one each for upstream and downstream flanking sequences. The ends of each individual flanking sequence were tagged to prevent the joining of sequences that may create a homopolymeric tract artefact between two sequences.
Individual files were analysed using the program Poly  [34] , open source software publically available from www. bioinformatics. org/poly. Non-overlapping homopolymer tracts of all four types are counted by Poly for the entire file and a number of parameters are then calculated, including: the total base count for each file, its GC composition, and the numbers and the frequencies of the homopolymer tracts of different lengths. A moving window of 1 bp in length is used by Poly to differentiate tracts and spacers, taking into account the tags used to prevent artifactual sequence concatenation. These data and additional information are kept as data objects in the program and can be manipulated in various ways. Since Poly has been described in detail in previous reports  [3, 34] , we next only define its parameters that were used in this study.
The log (R) vs N plots were generated using GraphPad Prism v6. 0 (GraphPad Software, La Jolla, USA). Linear interpolation of the data was used to determine the values of N at logR values of 0. 5 (defined here as the threshold for over-representation). The slope of over-representation (slope R ) was determined by the same linear interpolation of R between the threshold for over-representation and N max obs of each tract type. To reduce the noise in the analysis associated with infrequent observations of very long tracts, N max obs is scored only when ci N obs ≥ 4. The maximum expected length of a homopolymer tract of any base N max exp, is calculated for any sequence length based upon random base sequence occurrence in a sequence of that length of equivalent base composition to the real sequence.
Calculating tract frequencies as a function of sequence position We developed a non-overlapping motif frequency counting program called motif. freq. pl. , written in perl v. 5. 12. 4. , which can be accessed at http://www. bioinformatics. org/ motiffreq. It calculates the individual bin frequencies of any specified input sequence motif within a binned sequence. Motif. freq. pl requires the user to enter the input sequence motif to be searched and the bin size. The input sequence(s) is divided evenly into sequence bins of size determined by the input bin size. The program will count the occurrences of the input sequence motif within each bin and return the values to the output file as a motif frequency defined as F obs , the number of motif occurrences/ nucleotides in the bin. If the motif is repeated in the sequence without interruption by intervening bases, motif.
freq. pl will count as many motifs as the program can detect. If the motif is physically located at the bin interface and occurs within two adjacent bins, the motif will be counted as being within the bin which contains the most bases of the motif. If the motif contains an equal number of bases located within two adjacent bins, the motif will be considered to reside within the first bin being counted in the sequence. The output of motif. freq. pl is a text file listing the bin number and motif frequency for each bin. We also created a sequence-shuffling program that conserves the original input sequence's base frequencies during shuffling. This program is called shuffle. pl, also written in perl v. 5. 12. 4. , and it can be accessed at http:// www. bioinformatics. org/motiffreq. The purpose of this program was to assess, by comparison, the significance of the motif.
freq. pl program's frequency-bin output resulting from the input of real sequences. The shuffling program reads multiple sequences of specified length in FASTA format and then merges all sequences together into one master combined string. The program then shuffles all bases in the combined string, using the shuffle function in the LIST::Util module in PERL. The shuffled master string is then broken up into the original number and length of sequences used as input. These shuffled sequences were then used as input to motif. freq. pl, producing output to allow exact comparison of the original sequence's frequency-bin distribution to the shuffled sequence's to assess for locations of motif enrichment or depletion. Shuffle. pl allows the user to specify the number of times that the motif shuffling is to be applied to the original input sequences.
Thus, for a large number of shufflings and by averaging the shuffled frequencies in equivalent bins, a much lower 'noise' or variation in the shuffled random frequency-bin distribution can be achieved to compare to the original sequence motif bin distribution. As a test, real sequences were input into the shuffle. pl program to generate ten-fold randomly shuffled sequences. For a number of calculated short sequence motif frequency-bin distributions, these control shuffled distributions all exhibited frequency vs bin # plots with low variation between bins. The linear fits to these plots possessed slopes near zero (R 2 < 0. 05), indicating no statistically significant trend in the shuffled sequential bin frequencies, as expected. In this study, we carried out 10 shufflings of each real sequence analyzed and used these as input to motif.
In other words, a few ECG samples were missing due to undetected causes occurring somewhere in the wireless/satellite transmission chain that are attributed to the fact that the different links involved (fixed access network, mobile access network and satellite DVB-RCS interfacing) are liable to inducing errors or loss on the transmitted data. Such data corruption/loss can occur anytime and anywhere. The timeout of several ARQ (Automatic Repeat Request) procedures was shown to induce packet loss: 1 -2% for GPRS, and 8% for the satellite  [43]. To cope with that problem, TeSA devised a recovering method which hybridized Papoulis-Gerchberg (PG) algorithm and an Auto-Regressive (AR)-based reconstruction algorithm. The principle of the PG exact reconstruction algorithm lies in an interpolation of the missing samples using the band-limited property of the ECG signal, via an iterative process which allows to replace the missing part of the signal with the result of the Inverse Fast Fourier Transform (IFFT).
Tested on the MIT-BIH Arrhythmia Database, the combined method yielded better performance than the PG and AR algorithms for missing parts of up to 30 consecutive samples (120 ms). The paper aims at identifying and qualitatively surveying all the different factors related to the wireless and satellite links that may be a cause of packet error or loss, and thus undermine the reconstruction performance of TeSA's algorithm, without any quantitative assessment at this stage. Packet errors and loss can be traced back to mainly three different sources: (i) general performance criteria of the transmission system; (ii) wireless issues; (iii) satellite link issues. σ 2 xgap σ.
DVB-S2-based air interface This section describes a DVB-S2-based adaptive air interface designed by TeSA in the framework of an R&T contract with the French Space Agency (CNES) to meet the performance constraints of bidirectional satellite communication links to be established in a post-disaster emergency situation in Ku/Ka and Q/V bands where strong channel impairments occur. The proposed solution allows to establish very quickly a minimum low bit rate satellite return link, using the available resources of a primary geostationary satellite system, and very small, low-cost and powerlimited dedicated ground terminals. The bi-directional transmission link is modeled within the Juzzle open source environment software with an emphasis on the return channel, deploying an adaptive strategy based on the DVB-S2 adaptive coding and modulation (ACM) scheme.
This section expounds the enhanced DVB-S2-like air interface proposed to support telemedicine applications in an emergency situation in a severely impaired channel environment in high frequencies; it also outlines the combined Excel/Juzzle/Matlab highlevel transmission link software simulation platform that was developed in order to assess the performance of the proposed transmission scheme. The simulator architecture follows a cross-layer approach, integrating propagation, DVB-S2-based physical layer, and traffic components. Some simulation results are also provided, emphasizing on the adopted adaptive strategy.
This thus raises some performance challenges to be coped with. Since the considered applications all were assumed to be IPbased ones, the DVB-S2 waveform was coupled with an efficient encapsulation mechanism, namely the GSE (Generic Stream Encapsulation) protocol at the Segmentation and Reassembly (SAR) layer, aimed at segmenting network layer IP datagrams (PDUs or Payload Data Units) into link layer DVB-S2 basic data units called BBFRAMEs (base band frames). The GSE mechanism was designed with the purpose of fully taking advantage of the innovative features of the DVB-S2, primarily in terms of reliability, flexibility, and enhanced capacity. MPE (Multi-Protocol Encapsulation) and ULE (Unidirectional Lightweight Encapsulation) have been the standard encapsulation techniques that were classically used in DVB-typed satellite systems, and as such they received abundant attention in the literature.
Nonetheless, GSE constitutes a much more efficient encapsulation scheme fitted to the DVB-S2 standard in that it allows to fully exploiting the adaptive ACM capability, implementing QoS scheduling decisions and flexible placement and enhanced fragmentation of PDUs in the flow  [27]. In particular, DVB-S2 GS (Generic Stream) data flows may be packetized or continuous streams. The first ones are suited to carrying PDUs of constant size, whereas the latters were designed to seamlessly adapt to input stream of any format, including continuous bit streams and variable-sized PDUs such as IP datagrams. GSE can avoid using MPEG2 packets as with MPE and ULE, which would be sub-optimal in the framework of DVB-S2. In effect, the GS flow is more suited to interactive services due to a liberty from inadequate MPEG2-TS constraints of constant bit rate and endto-end delay.
As a result, that means that a standard DVB-S2 transmitter cannot be used as a black box, but that the transmission chain must undergo some design adaptations, so as to conform to the provision envisaged in clause 5. 1 of the mobile version of the DVB-RCS standard  [6]. The Juzzle core component. The Juzzle core component is composed of 5 different nodes (Gateway, Satellite, GatewaySiteDiversitySlave, User terminal 1, and User terminal 2) as shown in Figure  3  hereafter: This core processing module was developed in Java due to the portability, reusability, and object-oriented feature of the programming language. The module uses the Java event engine allowing to model the various delays within the system more easily. The module models the emergency satellite system at high level as shown in Figure  6 , with the following nodes: two user terminals ("User terminals 1 and 2"), the master gateway, the slave gateway (to be switched to in case of strong impairments above a defined threshold when site diversity (SD) is activated) and the satellite, especially in terms of radio packet transmission, and its related link budget computation functions.
4. the IP aggregate traffic source is modeled by a Fractional Gaussian Noise (FGN) using the Fast Fourier Transform (FFT) and Paxson's FFT algorithm. Paxson's FFT method  [33]  consists in synthesizing a sample path having a same power spectral density (PSD) as an FGN process. This sample path can then be used in simulations as traces of real self-similar traffic. The algorithm relies on an implementation of Paxon's selfsimilar generator written in ANSI C, and provided with in the form of a routine fft_fgn. c developed by Christian Schuler  [33]. Adaptive strategy module. The adaptive strategy mechanism is at the heart of the simulator, and relies on a combination of several techniques aimed at ensuring a high availability of the transmission links in spite of severe channel impairments in the selected frequency bands (eg.
It involves DS-SS technique and other adaptive mechanisms such power control, and site diversity for a multibeam, bent-pipe satellite system. It was designed to rapidly establish a low bit rate link for emergency communications in Ku/Ka and Q/V bands. Link budget analyses have shown that even though SS may be deactivated, very low transmit power user terminals UTA and UTB yield reasonable performance for the envisaged purpose up to the Q band, but for rather moderate channel attenuation values. This highlights the relevance and efficiency of a solution combining ACM, SS, bit reduction, and SD techniques in a new adaptive strategy in order to improve the transmission performance. Such an adaptive strategy has been successfully implemented within the more general framework of an integrated Excel/Juzzle/Matlab software simulation platform designed to model the system in a high level cross-layer approach mixing propagation, physical layer, and higher layers components.
General description. A software model of the enhanced DVB-S2 transmission link was developed in mixed standard C and Java languages within an open source software environment called Juzzle [24]. The whole simulation platform was an integrated Excel/Juzzle/Matlab software package which also implements the C DIS-LIN [30] data plotting library. The Juzzle simulation platform The Juzzle simulation platform is composed of two separate and standalone Juzzle components: a channel propagation time series generator component and a processing core component, and of an extern postprocessing Matlab routine. Off-line propagation module. The propagation channel time series generation module is a pre-processing Juzzle component allowing to generate an attenuation time series configurable with a number of user parameters.
SO-DARs and LiDARs are very interesting options for the industry. For instance, they can measure wind speeds at high altitudes (up to 200 m) and this for many heights simultaneously. Over relatively flat terrains, remote sensing devices showed good performances when compared to cup anemometers  [2]. Despite these advantages, there is one main drawback associated to them. While retrieving wind speed, wind flow within the sampled volume is assumed to be homogeneous, which entails serious error over complex terrain  [3, 4]. Among proposed solutions  [3] , it is Article published by EDP Sciences suggested to model the error with the help of numerical models such as WAsP Engineering. In the present study, this approach was revisited using the open source CFD toolbox OpenFOAM. The main objective of this work was to evaluate the LiDAR error over complex terrain covered with forest with the aid of OpenFOAM in order to compare the results to experimental data and results obtained with the commercial softwares MeteoDyn and WAsP Engineering.
Evaluation of the model over complex terrain The LiDAR used for the present study is located in Anse-à-Valleau (AAV), Gaspe Peninsula on a complex site almost entirely covered with dense forest. Terrain complexity was analysed using IEC 61400-12-2 draft standard considering topography up to a range of 340 m around the remote sensor (see Fig. 5 ), which corresponds to 8 times the radius of the scanned disc when the instrument shoots at 80 m. It was classified as being moderately (Class 2) to highly (Class 4) complex. In order to evaluate the performance of the model, data from a measurement campaign undertaken from the 14/12/2007 to 29/12/2009 were used. More precisely, a flow simulation was run for all 10 • directions where experimental data were available, i. e. [270 • -350 • ]. The calculated ratio of horizontal velocity between two cup anemometers was compared to experimental measurements for each wind direction.