Find research datasets worth reusing

opencc-by-4.0Dec 2021View details →

[Data from:] Hypersensitive-like response in Brassica plants is specifically induced by molecules from egg-associated secretions of cabbage white butterflies

Characterization at physiological and molecular level of a HR-like cell death induced by Pieris spp. butterfly eggs in Brassica plants.

dryad40/100

Code and data from: A hierarchical approach for estimating state-specific mortality and state transition in dispersing animals with incomplete death records

Unbiased mortality estimates are fundamental for testing ecological and evolutionary theory as well as for developing effective conservation actions. However, mortality estimates are often confounded by dispersal, especially in studies where dead-recovery is not possible. In such instances, missing individuals (i.e. individuals with unobserved time of death) may have died or permanently emigrated from a study area, making inferences about their fate difficult. Mortality before and during dispersal, as well as the decision to disperse, usually depend on a suite of individual, social, and environmental covariates, which in turn can be used to draw conclusions about the fate of missing individuals. Here, we propose a Bayesian hierarchical model that takes into account time-varying covariates to estimate transitions between life-history states and mortality in each state using mark-resighting data with missing individuals. Specifically, our framework estimates mortality rates in two states (resident and dispersing state) by treating the fate of missing individuals as a latent (i.e. unobserved) variable that is statistically inferred based on information from individuals with a known fate and given the individual, social, and environmental conditions at the time of disappearance. Our model also estimates rates of state transition (i.e. emigration) to assess whether a missing individual was more likely to have died or survived due to unobserved emigration from the study area. We used simulations to check the validity of our model and assessed its performance with data of varying degrees of uncertainty. Our modeling framework provided accurate mortality and emigration estimates for simulated data of different sample sizes, proportions of missing individuals, and resighting intervals. Variation in sample size appeared to affect the precision of estimated parameters the most. Our approach offers a solution to estimating unbiased mortality of both resident and dispersing individuals as well as the probability of emigration using mark-resighting data with incomplete death records. Conditional on the availability of data on known-fate individuals and relevant time-varying covariates, our model can reconstruct the fate (death or emigration) of missing individuals. The modularity of our framework allows mortality analyses to be tailored to a variety of species-specific life histories.

opencc-zeroDec 2022View details →

Datasets of the manuscript "Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons"

DATASETS Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons Liliane S. Oliveira, Alejandro Reyes, Bas E. Dutilh and Arthur Gruber* * Correspondence: <a href="mailto:argruber@usp.br">argruber@usp.br</a> (AG); Tel. +55 11 3091 7274   Here we provide different data of Microviridae, Flavivirus and casposons used throughout the work: <ul> <li>Microviridae folder <ul> <li>conserved_HMMs – profile HMMs constructed with TABAJARA in Conservation mode for Microviridae</li> <li>discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for Microviridae</li> <li>sequences – different sequence datasets and respective multiple sequence alignments <ul> <li>Microviridae_113-seq_training_set.fasta - 113 VP1 sequences covering diversity of the Microviridae family</li> <li>Microviridae_113-seq.aln – multiple sequence alignment of the 113-protein dataset</li> <li>Microviridae_1836-seq_testset.fasta - 1,836 sequence dataset covering 1,836 sequences of the major capsid protein (VP1) comprising 501 Alpavirinae sequences, 1,040 Gokushovirinae sequences and 295 Pichovirinae sequences</li> <li>Microviridae_1866-seq.aln - multiple sequence alignment of the 1,866-protein Microviridae dataset used in the experiment of Figure 4</li> </ul> </li> </ul> </li> <li>Flavivirus folder <ul> <li>conserved_HMMs – profile HMMs constructed with TABAJARA in Conservation mode for Flavivirus</li> <li>discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for Flavivirus <ul> <li>full-length – models constructed from full-length protein sequences</li> <li>short - models constructed from selected short alignment blocks of the protein sequences</li> </ul> </li> <li>sequences – different sequence datasets and respective multiple sequence alignments <ul> <li>Flavivirus_127-seq_training_set.fasta - 127 polyprotein sequences covering species diversity of the genus Flavivirus</li> <li>Flavivirus_127-seq.aln – multiple sequence alignment of the 127-protein dataset</li> <li>Flavivirus_6364-seq_testset.fasta - 6,364 sequence dataset covering species diversity of Flavivirus, including 3,919 of dengue virus (DENV), 327 of Zika virus (ZIKV), 63 of yellow fever virus (YFV), and the remaining 2,055 sequences covering other available flaviviruses</li> <li>Flavivirus_6364-seq.aln - multiple sequence alignment of the 6,364-protein Flavivirus dataset</li> </ul> </li> </ul> </li> <li>Casposons folder <ul> <li>casposon_generic_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for the generic detection of all casposons and discrimination from CRISPRs.</li> <li>casposon_family_discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for the specific discrimination among casposon families and from CRISPRs.</li> <li>sequences – different sequence datasets and respective multiple sequence alignments <ul> <li>casposons_crisprs.fasta – 106 Cas1 bona fide sequences derived from 52 CRISPRs and 54 casposons</li> <li>casposon_family_discrimination.aln - multiple sequence alignment of 52 bona fide CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for the discrimination of each casposon family.</li> <li>casposons_crisprs_discrimination.aln - multiple sequence alignment of 52 bona fide CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for discrimination of CRISPRs and casposons.</li> </ul> </li> </ul> </li> </ul>

opencc-by-4.0May 2022View details →

Data-set of the partial pressure of CO2, dissolved concentrations of CH4, N2O, NO3-, NO2- and NH4+, specific conductivity and water temperature in the rivers and streams of the Napo River basin in Ecuador (2018, 2019, 2020, 2021)

Data-set consists of two files: - data_ghgs.xlsx : Time-stamped and georeferenced data-set of the partial pressure of CO2 (pCO2 in ppm), dissolved CH4 concentration (CH4 in nmol/L), dissolved N2O concentration (N2O in nmol/L), specific (Sp.) conductivity (in µS/cm), water temperature (in °C), dissolved nitrate concentration (NO3- in µmol/L), dissolved nitrite concentration (NO2- in µmol/L), and dissolved ammonia concentration (NH4+ in µmol/L) in the rivers and streams of the Napo River basin in Ecuador (October 2018 and 2019, January 2019 and 2020, April 2019 and 2021, July 2019 and 2020). Gas measurements were made by headspace equilibration directly in the field with a infra-red gas analyser for CO2 and in the lab with a gas chromatograph for CH4 and N2O. NO3-, NO2- and NH4+ were measured with standard colometric procedures. Sampling and analytical protocols are provided here <a href="https://doi.org/10.5194/bg-16-3801-2019">https://doi.org/10.5194/bg-16-3801-2019</a> - RiverATLAS.xlsx: hydro-environmental data for the sampled streams extracted from RiverATLAS (https://www.nature.com/articles/s41597-019-0300-6). Data codes and units are available here: https://data.hydrosheds.org/file/technical-documentation/HydroATLAS_TechDoc_v10_1.pdf First column of each of the two files provides station ID allowing to merge both data-sets.

Degenerative Cervical Myelopathy (DCM) induces sex-specific dysbiosis in the mouse gut bacterial microbiome, altering abundance and function

Background: Degenerative cervical myelopathy (DCM) represents the commonest cause of spinal cord impairment induced by non-traumatic events in the elderly population. It describes a spectrum of disorders that cause progressive spinal cord compression, neurological impairment, loss of bladder and bowel functions, as well as gastrointestinal dysfunction. The gut microbiota has been increasingly recognized as an environmental factor that can modulate both the central nervous system and immune response through the microbiota-gut-brain axis. Changes in gut microbiota composition or in the microbiota producing factors have been linked in the progression and development of several different pathologies such as traumatic spinal cord injury (SCI). Little is known about the molecular mechanisms that trigger DCM manifestation, and the potential role of the gut microbiota. Results: Herein DCM was induced in female and male C57BL/6 mice by implanting an aromatic polyether material underneath the C5-6 laminae. The extent of DCM-induced changes in microbiota composition, also known as dysbiosis, was assessed by 16S rRNA sequencing from fecal samples at 3 different time points (6, 9 and 12 weeks after DCM induction). Several bacterial members were identified based on BLAST against the largest collection of metagenome-derived genomes from the mouse gut up to date. In both, female and males DCM caused gut dysbiosis compared with the sham group. However, dysbiosis was more pronounced in males than females, where several bacterial members of the families Lachnospiraceae and Muribaculaceae were significantly altered in the DCM group. These changes were also associated with altered immune cell composition in gut-associated lymphoid tissue, blood, and microbe-derived metabolic changes in propionate, butyrate, and lactate-producing bacterial members. Conclusions: Our results demonstrate for the first time that DCM causes dynamic changes over time in the gut microbiota. Furthermore, we identify specie-specific abundance changes during DCM progression. DCM strongly reduces the abundance of butyrate-producing bacteria, and lactate-producing bacteria in much less extent. Sequence-based pangenomics cores were not resolved between the latter bacteria, but the gap-filling reactions and metabolic modelling successfully identified pyruvate-to-butanoate and pyruvate-to-propionate genes such as Buk and ACH1, respectively. These results aid to better understand markers and the molecular mechanisms that over time trigger DCM manifestation in females and males.

Gene expression and splicing counts from the Yepez, Gusic et al study - fibroblast, hg19, strand-specific, low seq depth

File description: <ol> <li> geneCounts: gene-level counts  </li> <li> k_j: split counts spanning from one exon to another. </li> <li> k_theta: non-split counts covering a splice site </li> <li> n_psi3: total split counts from a given acceptor site </li> <li> n_psi5: total split counts from a given donor site </li> <li> n_theta: total split and non-split counts for a given splice site </li> <li> Sample annotation describing each sample from the dataset </li> <li> Description file with global information from the dataset </li> </ol> The gene counts were originated using the GTF file from release 34 of GENCODE <a href="https://www.gencodegenes.org/human/release_34">https://www.gencodegenes.org/human/release_34</a>, and the split and non-split counts contain only the annotated junctions from the same release. Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (<a href="https://github.com/gagneurlab/drop">https://github.com/gagneurlab/drop</a>). Number of samples: 127 Tissue: Fibroblast Organism: Homo sapiens Genome assembly: hg19 Gene annotation: gencode34 Median mapped reads: 71 million Disease (ICD-10: N): E88: 84, NONE: 12, F89: 6, G31: 3, R27: 3, E72: 3, G40: 2, R16: 2, K72: 2, P94: 2, E77: 1, E75: 1, G71: 1, G93: 1, Q78: 1, G82: 1, R29: 1, Q02: 1 Strand specific: True Paired end: True Dataset contact: Vicente Yepez, yepez at in.tum.de; Christian Mertes, mertes at in.tum.de; Julien Gagneur, gagneur at in.tum.de; Holger Prokisch, prokisch at helmholtz-muenchen.de Citation: Cite both the resource using Zenodo's citation and the publication under References

Gene expression and splicing counts from the Yepez, Gusic et al study - fibroblast, hg19, strand-specific, high seq depth

File description: <ol> <li> geneCounts: gene-level counts  </li> <li> k_j: split counts spanning from one exon to another. </li> <li> k_theta: non-split counts covering a splice site </li> <li> n_psi3: total split counts from a given acceptor site </li> <li> n_psi5: total split counts from a given donor site </li> <li> n_theta: total split and non-split counts for a given splice site </li> <li> Sample annotation describing each sample from the dataset </li> <li> Description file with global information from the dataset </li> </ol>   The gene counts were originated using the GTF file from release 34 of GENCODE <a href="https://www.gencodegenes.org/human/release_34">https://www.gencodegenes.org/human/release_34</a>, and the split and non-split counts contain only the annotated junctions from the same release. Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (<a href="https://github.com/gagneurlab/drop">https://github.com/gagneurlab/drop</a>). Number of samples: 135 Tissue: Fibroblast Organism: Homo sapiens Genome assembly: hg19 Gene annotation: gencode34 Median mapped reads: 116 million Disease (ICD-10: N): E88: 112, G31: 8, NONE: 5, K72: 2, G71: 2, E72: 1, G93: 1, I42: 1, F82: 1, E75: 1, F89: 1 Strand specific: True Paired end: True Dataset contact: Vicente Yepez, yepez at in.tum.de; Christian Mertes, mertes at in.tum.de; Julien Gagneur, gagneur at in.tum.de; Holger Prokisch, prokisch at helmholtz-muenchen.de Citation: Cite both the resource using Zenodo's citation and the publication under References

opencc-by-4.0Sep 2021View details →

Summary statistics of cell-type specific cis-eQTLs in eight brain cell-types

This dataset contains eQTL summary statistics for all SNPs-gene pairs in 8 major brain cell types (within 1MB window surrounding the TSS of each expressed gene). For each cell type, there is one file per chromosome. Column description: 1. Gene_id 2. SNP_id 3. Distance to TSS 4. Nominal p-value 5. Beta In addition, a file contains the SNP positions (snp_pos.txt) and tested allele. Update February 2023: The summary statistics from our 'tissue-like' analysis were added (pb[1-22].gz). These file contain eQTL summary statistics after aggregating all reads from all nuclei for each individual (instead of per cell type).

opencc-by-4.0Jan 2023View details →

Examining litter specific variability in mice and its impact on neurodevelopmental studies

Our current understanding of litter variability in neurodevelopmental studies using mice may limit translation of neuroscientific findings. Higher variance of measures across litters than within, often termed intra-litter likeness, may be attributable to both pre- and postnatal environment. This study aimed to assess the litter-effect within behavioral assessments (2 timepoints) and anatomy using T1-weighted magnetic resonance images across 72 brain region volumes (4 timepoints) (36 C57bl/6J inbred mice; 7 litters: 19F/17M). Between-litter comparisons of brain and behavioral measures and their associations were evaluated using univariate and multivariate techniques. A power analysis using simulation methods was then performed on modeled neurodevelopment and to evaluate trade-offs between number-of-litters, number-of-mice-per-litter, and sample size. Our results show litter-specific developmental effects, from the adolescent period to adulthood for brain structure volumes and behaviors, and for their associations in adulthood. Our power simulation analysis suggests increasing the number-of-litters in experimental designs to achieve the smallest total sample size necessary for detecting different rates of change in specific brain regions. Our results demonstrate how litter-specific effects may influence development and that increasing the litters to the total sample size ratio should be strongly considered when designing neurodevelopmental studies. You will find the dataset descriptive information and MAGeT brain label volumes. Please consult the readme.txt file for a thorough description of the different csvs shared below.

Part 1: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogens'

Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory. The file Data.One.Focb-2.tar contains 22 files of paired-end reads from F. oxysporum f.sp. cubense tropical race 1 isolate N2 (SRA accession: SRR550150, SRR550151), and F. oxysporum f.sp. cubense TR4 isolates Hainan.B2 (SRR550152), My-1 (SRR7226877), La-2 (SRR7226878), Vn-2 (SRR7226879), Leb1.2C (SRR7226880), JV11 (SRR7226881), Phi2.6C (SRR7226882), Pak1.1A (SRR7226883), UK0001 (SRR9733598).

Part 2: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogens'

Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory. The file Data.One.Focb.tar contains 16 files of paired-end reads from F. oxysporum f.sp. cubense TR4 isolates II-5 (SRA accession: SRR10054446), S1B8 (SRR10054447), JV14 (SRR10054448), FOC.TR4-5 (SRR10054449), FOC.TR4-1 (SRR10054450), Col2 (SRR10103605), Col4 (SRR10125423), Col17 (SRR10747097).

opencc-by-4.0Jan 2023View details →

Part 4: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogen

Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory. The file reads.tar contains 44 files of paired-end reads from F. oxysporum f.sp. lycopersici isolate Fol069 (SRA accession: SRR307106, SRR307107, SRR307113, SRR307115, SRR307123, SRR307257, SRR307266), isolate Fol072 (SRR307122, SRR307092, SRR307091, SRR307090, SRR307086, SRR307281, SRR307250), isolate Fol4287 (SRR7690004, SRR3139043), and F. oxysporum f.sp. radicis-cucumerinum isolate Forc016 (SRR3139027, SRR3139028), isolate Forc024 (SRR3139029, SRR3139030), isolate Forc031 (SRR3139031, SRR3139032).

opencc-by-4.0Apr 2022View details →

Code for the paper "First-Class Data Types in Shallow Embedded Domain-Specific Languages using Metaprogramming": IFL 2022

Code accompanying the paper First-Class Data Types in Shallow Embedded Domain-Specific Languages using Metaprogramming. All code is Haskell code, tested with GHC 8.8.4 <ul> <li>./tuple: contains the examples from Section 3.2</li> <li>./bin: contains the examples from Section 5.1</li> <li>./artifact: contains an extended version of the running example of the paper  </li> </ul>

opencc-by-4.0Jan 2023View details →

Replication package for The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

In order to provide reproducibility, we have made all the data collected in the study titled: "The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review" as a replication package. This package includes the following files: <ol> <li>A zip file containing the codes used for this Systematic Literature Review from NVIVO software. One separate file for each of the codes in the Zip file. (Code Summary.zip)</li> <li>Data collection form for different rounds of study. (Data_Collection_Form_Final.xlsx)</li> <li>Summary of number of papers retrieved in each round. (Number_of_Retrieved_studies.pdf)</li> </ol>

VReqST - Requirement Specification Tool Support for Virtual Reality Products

Virtual Reality (VR) Environments are challenging to build with discrete and incremental requirements. VR practitioners often need human assistance to achieve product completeness, as most VR requirements are either abstract or under specified. The slightest change to these requirement specifications tends to drastically impact the overall control-flow of the product. It exponentially increases the development cost. To address the completeness of specifying VR product requirements, we introduce VReqST, a tool for specifying requirements for VR software products. We use role base model template of bare-minimum VR Software to auto-provision all dimensions of VR as a domain on specifying VR product requirements. This tool avoids ambiguity while specifying requirements and provides seamless VR product development.

Datset related to article "G507D MUTATION IN FUS GENE CAUSES FAMILIAL AMYOTROPHIC LATERAL SCLEROSIS WITH A SPECIFIC GENOTYPE-PHENOTYPE CORRELATION"

NGS_analysis performed at Fondazione Besta carried out as part of the study reported at title

opencc-zeroFeb 2023View details →

dryad40/100

Patient-specific induced pluripotent stem cell properties implicate Ca2+-homeostasis in clinical arrhythmia associated with combined heterozygous RYR2 and SCN10A variants

We illustrate the use of induced pluripotent stem cells (iPSCs) as platforms for investigating cardiomyocyte phenotypes in a human family pedigree exemplified by novel heterozygous RYR2-A1855D and SCN10A-Q1362H variants occurring alone and in combination. The proband, a four-month-old boy, presented with polymorphic ventricular tachycardia (PVT). Genetic tests revealed double novel heterozygous RYR2-A1855D and SCN10A-Q1362H variants inherited from his father (F) and mother (M) respectively. His father showed ventricular premature beats (VPB); his mother was asymptomatic. Molecular biological characterisations demonstrated greater TNNT2 mRNA expression in the iPSCs-induced cardiomyocytes (iPS-CMs) than in the iPSCs. cTNTs became progressively organised, but cytoplasmic RYR2 and SCN10A aggregations occurred in the iPS-CMs. Proband-specific iPS-CMs showed decreased RYR2 and SCN10A mRNA expression. The RYR2-A1855D variant resulted in premature spontaneous sarcoplasmic reticular (SR) Ca2+ transients (PCTs), Ca2+ oscillations (COs), and increased action potential durations (APDs). SCN10A-Q1362H did not confer any specific phenotype. However, the combined heterozygous RYR2-A1855D and SCN10A-Q1362H variants in the proband iPS-CMs resulted in accentuated Ca2+ homeostasis disorders, AP prolongation and susceptibility to early afterdepolarisations (EADs) at high stimulus frequencies. These findings attribute the clinical phenotype in the proband to effects of the heterozygous RYR2 variant exacerbated by heterozygous SCN10A modification.

Earthquake catalogs for: A specific earthquake processing workflow for studying long-lived explosive volcanic eruptions with application to the 2008 Okmok eruption

Repository for the seismic catalogs from Garza-Giron et al. (2023a,b). These include the catalog with absolute locations using NonLinLoc (Lomax et al., 2001; Lomax and Curtis, 2001), and the relocated catalogs using hypoDD (Waldhauser and Ellsworth, 2000) and GrowClust (Trugman and Shearer, 2017). The header of the CSV files is as follows: Date (year/month/day), Time (hr:min:sec:msec), Latitude (decimal degrees), Longitude (decimal degrees), Depth (km), Magnitude (Ml calculated for this study), Event_type (VT:vulcano-tectonic;LP:long-period), Number of stations where the event was detected, ID References: <div>Garza‐Giron, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023a). A specific earthquake processing workflow for studying long‐lived, explosive volcanic eruptions with application to the 2008 Okmok Volcano, Alaska, eruption. Journal of Geophysical Research: Solid Earth, e2022JB025882.</div> <div> </div> <div> <div>Garza‐Girón, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023b). Earthquakes record cycles of opening and closing in the enhanced seismic catalog of the 2008 Okmok Volcano, Alaska, eruption. Journal of Geophysical Research: Solid Earth, 128(7), e2023JB026893.</div> <div> </div> </div> Lomax A, Curtis A (2001) Fast, probabilistic earthquake location in 3-D models using oct-tree importance sampling. Geophys Res Abstracts, 3:955. Lomax, A., Zollo, A., Capuano, P., and Virieux, J. (2001). Precise, absolute earthquake location under Somma‐Vesuvius volcano using a new 3D velocity model.Geophysical Journal International,146, 313–331. Trugman, D. T., and Shearer, P. M. (2017). GrowClust: A hierarchical clustering algorithm for relative earthquake relocation, with application to the Spanish Springs and Sheldon, Nevada, earthquake sequences. Seismological Research Letters, 88(2A), 379-391. Waldhauser, F., and Ellsworth, W. L. (2000). A double-difference earthquake location algorithm: Method and application to the northern Hayward fault, California. Bulletin of the Seismological Society of America, 90(6), 1353-1368.

Dataset related to article"G507D MUTATION IN FUS GENE CAUSES FAMILIAL AMYOTROPHIC LATERAL SCLEROSIS WITH A SPECIFIC GENOTYPE-PHENOTYPE CORRELATION"

NGS Analyses of patients included in the study reported at title followed at Fondazione Besta

Non-systematic literature review of challenges that hinder the implementation of specific targets of the BDS 2030

In the BioAgora project, Deliverable 1.1 focused on assessing and categorizing the challenges that can hinder the implementation of the EU Biodiversity Strategy 2030. A mixed-method research strategy was used to collect evidence on existing challenges, including a general and a targeted (non-systematic) literature review. This database summarizes the results of this non-systematic literature review as well as expert opinion shared on the initial results by project consortium members. The general literature search was carried out between the 1st September and the 10th October 2022, and contained the fixed keywords EU, European, biodiversity, conservation, strategy, implementation, evaluation as well as the interchangeable terms barrier, challenge, and issue. This search returned approximately 16,800 results of which the abstracts of the first 70 hits were screened for relevant guidance to establish the broad challenge categories. After the broad challenge categories were established, we launched a targeted literature search from the 10th October until the 5th November 2022. Here, a series of searches with the fixed terms EU, biodiversity, implementation, [target-specific input, e.g. invasive species, soil ecosystems, freshwater ecosystems] and the interchangeable terms challenge, barrier, and issue was conducted. Per search, the abstracts of the initial 15 results were screened and detailed information from the publications with relevance to the research question were extracted. Both searches included only publications from 2010 onwards and if possible, more recent publications were prioritised over older ones.