119 10 20655 https://www.socictopen.socict.org/files/original/f6fc09b803a3e9a7358a71f4f3d4b713.pdf 531c77d74f699c6f7571df467b25d2be Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Better quality score compression through sequence-based quality smoothing Creator An entity primarily responsible for making the resource Yoshihiro Shibuya, Matteo Comin Description An account of the resource Abstract Motivation Current NGS techniques are becoming exponentially cheaper. As a result, there is an exponential growth of genomic data unfortunately not followed by an exponential growth of storage, leading to the necessity of compression. Most of the entropy of NGS data lies in the quality values associated to each read. Those values are often more diversified than necessary. Because of that, many tools such as Quartz or GeneCodeq, try to change (smooth) quality scores in order to improve compressibility without altering the important information they carry for downstream analysis like SNP calling. Results We use the FM-Index, a type of compressed suffix array, to reduce the storage requirements of a dictionary of k-mers and an effective smoothing algorithm to maintain high precision for SNP calling pipelines, while reducing quality scores entropy. We present YALFF (Yet Another Lossy Fastq Filter), a tool for quality scores compression by smoothing leading to improved compressibility of FASTQ files. The succinct k-mers dictionary allows YALFF to run on consumer computers with only 5.7 GB of available free RAM. YALFF smoothing algorithm can improve genotyping accuracy while using less resources. Availability https://github.com/yhhshb/yalff Date A point or period of time associated with an event in the lifecycle of the resource 2019 Subject The topic of the resource FASTQ compression, BWT, FM-Index Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s12859-019-2883-5 Source A related resource from which the described resource is derived BMC Bioinformatics Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Computer applications to medicine. Medical informatics Language A language of the resource EN https://www.socictopen.socict.org/files/original/7eaa348fd89461a0472f62946fca101f.pdf d560b7f9c6ecd33f8d58796baf1a1127 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The effectiveness of contact tracing in emerging epidemics. Creator An entity primarily responsible for making the resource Don Klinkenberg, Christophe Fraser, Hans Heesterbeek Description An account of the resource BACKGROUND: Contact tracing plays an important role in the control of emerging infectious diseases, but little is known yet about its effectiveness. Here we deduce from a generic mathematical model how effectiveness of tracing relates to various aspects of time, such as the course of individual infectivity, the (variability in) time between infection and symptom-based detection, and delays in the tracing process. In addition, the possibility of iteratively tracing of yet asymptomatic infecteds is considered. With these insights we explain why contact tracing was and will be effective for control of smallpox and SARS, only partially effective for foot-and-mouth disease, and likely not effective for influenza. METHODS AND FINDINGS: We investigate contact tracing in a model of an emerging epidemic that is flexible enough to use for most infections. We consider isolation of symptomatic infecteds as the basic scenario, and express effectiveness as the proportion of contacts that need to be traced for a reproduction ratio smaller than 1. We obtain general results for special cases, which are interpreted with respect to the likely success of tracing for influenza, smallpox, SARS, and foot-and-mouth disease epidemics. CONCLUSIONS: We conclude that (1) there is no general predictive formula for the proportion to be traced as there is for the proportion to be vaccinated; (2) variability in time to detection is favourable for effective tracing; (3) tracing effectiveness need not be sensitive to the duration of the latent period and tracing delays; (4) iterative tracing primarily improves effectiveness when single-step tracing is on the brink of being effective. Date A point or period of time associated with an event in the lifecycle of the resource 2006 Identifier An unambiguous reference to the resource within a given context DOI: 10.1371/journal.pone.0000012 Source A related resource from which the described resource is derived PLoS ONE Publisher An entity responsible for making the resource available Public Library of Science (PLoS) Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/8be43c9befecb66fa6701763ef58267d.pdf 64fa61690012c766baf3df87b8ec8104 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Bacterial Outer Membrane Vesicles (OMVs)-Based Dual Vaccine for Influenza A H1N1 Virus and MERS-CoV Creator An entity primarily responsible for making the resource Mahmoud M. Shehata, Ahmed Mostafa, Lisa Teubner, Sara H. Mahmoud, Ahmed Kandeil, Rabeh El Shesheny, Thamer A. Boubak, Renate Frantz, Luigi La Pietra, Stephan Pleschka, Ahmed Osman, Ghazi Kayali, Trinad Chakraborty, Mohamed A. Ali, Mobarak Abu Mraheil Description An account of the resource Vaccination is the most functional medical intervention to prophylactically control severe diseases caused by human-to-human or animal-to-human transmissible viral pathogens. Annually, seasonal influenza epidemics attack human populations leading to 290−650 thousand deaths/year worldwide. Recently, a novel Middle East Respiratory Syndrome Coronavirus emerged. Together, those two viruses present a significant public health burden in areas where they circulate. Herein, we generated a bacterial outer membrane vesicles (OMVs)-based vaccine presenting the antigenic stable chimeric fusion protein of the H1-type haemagglutinin (HA) of the pandemic influenza A virus (H1N1) strain from 2009 (H1N1pdm09) and the receptor binding domain (RBD) of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) (OMVs-H1/RBD). Our results showed that the chimeric antigen could induce specific neutralizing antibodies against both strains leading to protection of immunized mice against H1N1pdm09 and efficient neutralization of MERS-CoV. This study demonstrate that OMVs-based vaccines presenting viral antigens provide a safe and reliable approach to protect against two different viral infections. Date A point or period of time associated with an event in the lifecycle of the resource 2019 Subject The topic of the resource OMVs, influenza vaccine, MERS-CoV, H1N1pdm Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/vaccines7020046 Source A related resource from which the described resource is derived Vaccines Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/77b06b7913d8da31c038abe0a3c17fb4.pdf 77e4181446053cfd571be90c61d588e8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Research on a Method for Simulating Multiview Ocean Wave Synchronization Data by Networked SAR Satellites Creator An entity primarily responsible for making the resource Yong Wan, Xiaoyu Zhang, Yongshou Dai, Xiao-Lei Shi Description An account of the resource It is expected that the problem of the azimuth cutoff wavelength in single-satellite synthetic aperture radar (SAR) observations can be solved by means of the cooperative observation of networked SAR satellites. Multiview SAR wave synchronization data are required in the process. However, most of the current orbiting satellites are geosynchronous orbit satellites; the simultaneous observation by multiple SARs in the same sea area cannot be achieved, and multiview synchronization data cannot be obtained. Therefore, this paper studies the simulation of the multiview SAR wave synchronization data. Ocean wave spectra were simulated by using the Pierson Moskowitz (PM) spectrum. The Monte Carlo method was used to simulate two-dimensional (2D) ocean surfaces at different wind speeds. The two-scale electromagnetic scattering model was used to calculate the ocean surface backscattering coefficient, and the time-domain echo algorithm was used to generate echo signals. The echo signals were processed by the Range−Doppler (RD) imaging algorithm to obtain ocean SAR data. Based on the obtained single-SAR wave data, networked satellites consisting of three SARs were simulated, and the SAR wave data were synchronized. The results show that when SARs are used to observe the same sea area from different observation directions, the clarity of the wave fringes in the SAR images are different. For different azimuth angles, the degrees of azimuth cutoff are different. These results reflect the influences of different degrees of azimuth cutoff on SAR images. The simulated wave synchronization data can be used as the basic data source for subsequent azimuth cutoff wavelength compensation. Date A point or period of time associated with an event in the lifecycle of the resource 2019 Subject The topic of the resource networked SAR satellites, multi-view, SAR wave synchronization data simulation, azimuth cutoff Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/jmse7060180 Source A related resource from which the described resource is derived Journal of Marine Science and Engineering Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Naval architecture. Shipbuilding. Marine engineering, Oceanography Language A language of the resource EN https://www.socictopen.socict.org/files/original/ff69ba65fb945e1ad3d9c021790eb658.pdf 2f32939174c1b627f4eed99f635b6b9c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Transmissible gastroenteritis virus infection decreases arginine uptake by downregulating CAT-1 expression Creator An entity primarily responsible for making the resource LU Xia, Lei Dai, Qian Yang Description An account of the resource Abstract Transmissible gastroenteritis virus (TGEV) is a coronavirus that causes severe diarrhea in suckling piglets. TGEV primarily targets and infects porcine intestinal epithelial cells, which play an important role in nutrient absorption. However, the effects of TGEV infection on nutrient absorption in swine have not yet been investigated. In this study, we evaluated the impact of TGEV infection on arginine uptake using the porcine small intestinal epithelial cell line IPEC-J2 as a model system. High performance liquid chromatography (HPLC) analyses showed that TGEV infection leads to reduced arginine uptake at 48 hours post-infection (hpi). Expression of cationic amino acid transporter 1 (CAT-1) was attenuated as well. TGEV infection induced activation of phospho-protein kinase C α (p-PKC α), phospho-epidermal growth factor receptor (p-EGFR), and enhanced the expression of caveolin-1, all of which appear to be involved in down-regulating arginine uptake and CAT-1 expression. These results illuminate the relationship between TGEV infection and nutrient absorption, and further our understanding of the mechanisms of TGEV infection. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s13567-018-0591-1 Source A related resource from which the described resource is derived Veterinary Research Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Veterinary medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/2cb52864d3bdf5c7c27dbc190bf790aa.pdf ea78d951f66395795aba5c9cd2e28de8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Differential repression of alternative transcripts: a screen for miRNA targets. Creator An entity primarily responsible for making the resource Matthieu Legendre, William Ritchie, Fabrice Lopez, Daniel Gautheret Description An account of the resource Alternative polyadenylation sites produce transcript isoforms with 3' untranslated regions (UTRs) of different lengths. If a microRNA (miRNA) target is present in the UTR, then only those target-containing isoforms should be sensitive to control by a cognate miRNA. We carried out a systematic examination of 3' UTRs containing multiple poly(A) sites and putative miRNA targets. Based on expressed sequence tag (EST) counts and EST library information, we observed that levels of isoforms containing targets for miR-1 or miR-124, two miRNAs causing downregulation of transcript levels, were reduced in tissues expressing the corresponding miRNA. This analysis was repeated for all conserved 7-mers in 3' UTRs, resulting in a selection of 312 motifs. We show that this set is significantly enriched in known miRNA targets and mRNA-destabilizing elements, which validates our initial hypothesis. We scanned the human genome for possible cognate miRNAs and identified phylogenetically conserved precursors matching our motifs. This analysis can help identify target-miRNA couples that went undetected in previous screens, but it may also reveal targets for other types of regulatory factors. Date A point or period of time associated with an event in the lifecycle of the resource 2006 Identifier An unambiguous reference to the resource within a given context DOI: 10.1371/journal.pcbi.0020043 Source A related resource from which the described resource is derived PLoS Computational Biology Publisher An entity responsible for making the resource available Public Library of Science (PLoS) Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General) Language A language of the resource EN https://www.socictopen.socict.org/files/original/daf2c74679c012741a640b4ccb66a065.pdf 03f8f26807f48c2315167469418e598e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource microRNAs in viral acute respiratory infections: immune regulation, biomarkers, therapy, and vaccines Creator An entity primarily responsible for making the resource Stephen A. Leon-Icaza, Mingtao Zeng, Adrian G. Rosas-Taraco Description An account of the resource Abstract MicroRNAs (miRNAs) are single-stranded RNAs of 17–24 nt. These molecules regulate gene expression at the post-transcriptional level and are differentially expressed in viral acute respiratory infections (ARIs), which are responsible for high morbidity and mortality around the world. In recent years, miRNAs have been studied in order to discover anti-viral ARI drug targets as well as biomarkers for diagnosis, severity, and prognosis. This review presents an analysis of the regulatory response to viral ARIs of miRNAs, including their participation in the innate immune response, their utility as biomarkers, and their potential for future therapies and vaccine development. Date A point or period of time associated with an event in the lifecycle of the resource 2019 Subject The topic of the resource miRNA, Viral ARI, Rhinovirus, Influenza virus, hMPV, coronavirus Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s41544-018-0004-7 Source A related resource from which the described resource is derived ExRNA Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Therapeutics. Pharmacology Language A language of the resource EN https://www.socictopen.socict.org/files/original/677e4c032604a8e5f7084b364607c3bb.pdf 7903c8a161a272a597cd98bcaae35519 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Efficient computation of spaced seed hashing with block indexing Creator An entity primarily responsible for making the resource Samuele Girotto, Matteo Comin, Cinzia Pizzi Description An account of the resource Abstract Background Spaced-seeds, i.e. patterns in which some fixed positions are allowed to be wild-cards, play a crucial role in several bioinformatics applications involving substrings counting and indexing, by often providing better sensitivity with respect to k-mers based approaches. K-mers based approaches are usually fast, being based on efficient hashing and indexing that exploits the large overlap between consecutive k-mers. Spaced-seeds hashing is not as straightforward, and it is usually computed from scratch for each position in the input sequence. Recently, the FSH (Fast Spaced seed Hashing) approach was proposed to improve the time required for computation of the spaced seed hashing of DNA sequences with a speed-up of about 1.5 with respect to standard hashing computation. Results In this work we propose a novel algorithm, Fast Indexing for Spaced seed Hashing (FISH), based on the indexing of small blocks that can be combined to obtain the hashing of spaced-seeds of any length. The method exploits the fast computation of the hashing of runs of consecutive 1 in the spaced seeds, that basically correspond to k-mer of the length of the run. Conclusions We run several experiments, on NGS data from simulated and synthetic metagenomic experiments, to assess the time required for the computation of the hashing for each position in each read with respect to several spaced seeds. In our experiments, FISH can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.9x to 6.03x, depending on the structure of the spaced seeds. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Subject The topic of the resource Spaced seeds, Kmers, Efficient computation of hashing Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s12859-018-2415-8 Source A related resource from which the described resource is derived BMC Bioinformatics Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Computer applications to medicine. Medical informatics Language A language of the resource EN https://www.socictopen.socict.org/files/original/fdc99af5884cbdf358544e3514fc59b4.pdf 4dac655ddefd4cc90a5221c4f2effa58 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The viral aetiology of influenza-like illnesses in Kampala and Entebbe, Uganda, 2008 Creator An entity primarily responsible for making the resource Stephen Balinandi, Barnabas Bakamutumaho, John T. Kayiwa, Juliette Ongus, Joseph Oundo, Anna C. Awor, Julius J. Lutwama Description An account of the resource Background: As the threat of zoonoses and the emergence of pandemic-prone respiratory viruses increases, there is a need to establish baseline information on the incidence of endemic pathogens in countries worldwide. Objectives: To investigate the presence of viruses associated with influenza-like illnesses (ILI) in Uganda. Methods: A cross-sectional study was conducted in which nasopharyngeal swab specimens were collected from patients diagnosed with ILI in Kampala and Entebbe between 14 August2008 – 15 December 2008. A multiplex polymerase chain reaction assay for detecting 12 respiratory viruses was used. Results: A total of 369 patients (52.3% females) was enrolled; the median age was 6 years (range1–70). One or more respiratory viruses were detected in 172 (46.6%) cases and their prevalence were influenza A virus (19.2%), adenovirus (8.7%), human rhinovirus A (7.9%), coronavirusOC43 (4.3%), parainfluenza virus 1 (2.7%), parainfluenza virus 3 (2.7%), influenza B virus (2.2%),respiratory syncytial virus B (2.2%), human metapneumovirus (1.4%), respiratory syncytialvirus A (1.1%), parainfluenza virus 2 (0.5%) and coronavirus 229E (0.5%). There were 24 (14.0%) mixed infections. Conclusions: This study identified some of the respiratory viruses associated with ILI in Uganda.The circulation of some of the viruses was previously unknown in the study population. These results are useful in order to guide future surveillance and case management strategies involving respiratory illnesses in Uganda. Date A point or period of time associated with an event in the lifecycle of the resource 2013 Subject The topic of the resource viral infections, respiratory illness, Surveillance, Uganda Identifier An unambiguous reference to the resource within a given context DOI: 10.4102/ajlm.v2i1.65 Source A related resource from which the described resource is derived African Journal of Laboratory Medicine Publisher An entity responsible for making the resource available AOSIS Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Public aspects of medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/410b0c65ed4a369860cebbe0d2f51618.pdf 8de2b71856d8a8fad97e3becc0e7ea44 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource FSH: fast spaced seed hashing exploiting adjacent hashes Creator An entity primarily responsible for making the resource Samuele Girotto, Matteo Comin, Cinzia Pizzi Description An account of the resource Abstract Background Patterns with wildcards in specified positions, namely spaced seeds, are increasingly used instead of k-mers in many bioinformatics applications that require indexing, querying and rapid similarity search, as they can provide better sensitivity. Many of these applications require to compute the hashing of each position in the input sequences with respect to the given spaced seed, or to multiple spaced seeds. While the hashing of k-mers can be rapidly computed by exploiting the large overlap between consecutive k-mers, spaced seeds hashing is usually computed from scratch for each position in the input sequence, thus resulting in slower processing. Results The method proposed in this paper, fast spaced-seed hashing (FSH), exploits the similarity of the hash values of spaced seeds computed at adjacent positions in the input sequence. In our experiments we compute the hash for each positions of metagenomics reads from several datasets, with respect to different spaced seeds. We also propose a generalized version of the algorithm for the simultaneous computation of multiple spaced seeds hashing. In the experiments, our algorithm can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.6$$\times$$ × to 5.3$$\times$$ × , depending on the structure of the spaced seed. Conclusions Spaced seed hashing is a routine task for several bioinformatics application. FSH allows to perform this task efficiently and raise the question of whether other hashing can be exploited to further improve the speed up. This has the potential of major impact in the field, making spaced seed applications not only accurate, but also faster and more efficient. Availability The software FSH is freely available for academic use at: https://bitbucket.org/samu661/fsh/overview. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Subject The topic of the resource Spaced seeds, Kmers, Efficient hashing Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s13015-018-0125-4 Source A related resource from which the described resource is derived Algorithms for Molecular Biology Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Genetics Language A language of the resource EN