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11 results for “data reconciliation”
Replication data for: Reconciliation k-median: Clustering with non-polarized representatives
<p># Description<br> These files contain the data employed in the experiments described in Bruno Ordozgoiti and Aristides Gionis. 2019. Reconciliation k-median: Clustering with Non-Polarized Representatives. In Proceedings of the 2019 World Wide Web Conference (WWW’19), May 13–17, 2019, San Francisco, CA, USA.</p> <p>Twitter ID's have been anonymized.</p> <p># Contents<br> domain_mentions.txt: Each line contains a domain name, a user ID and the number of times this user has mentioned this domain name in a tweet.<br> format: domain_name <TAB> user_id <TAB> mention_count</p> <p>domains_ideology_score.txt: Domain names and their ideology score, estimated as described in (Lahoti et al. WSDM 2018). Note: missing scores can be retrieved from supplementary data in https://doi.org/10.1093/poq/nfw006<br> format: domain_name <TAB> ideology_score</p> <p>follow_graph.txt: The Twitter follower graph. Each line contains a user id and the user id of one of its followers.<br> format: user_id <TAB> follower_user_id</p> <p>representatives.txt: US Congress representatives, each with Twitter handle and polarity score computed using Barbera's method (Barbera, 2015).<br> format: rep_name <TAB> website_url <TAB> district <TAB> twitter_handle <TAB> party <TAB> barbera_polarity_score</p> <p>user_polarity.txt: User ID's and polarity score computed using Barbera's method (Barbera, 2015).<br> format: user_id <TAB> barbera_polarity_score</p>
Spreadsheets: step by step of data reconciliation
<p>Planilhas desenvolvidas para o artigo intitulado “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. Ele foi submetido no 26th IJCIEOM – International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. Na planilha “Database_IJCIEOM_2020” estão todos os dados usados na pesquisa.</p> <p>2. A planilha denominada “Coverage test” refere-se ao teste estatistico feito com a media dos blocos MT e FS.</p> <p>3. Em “<a href="http://ijcieom_2020.mt/">IJCIEOM_2020.MT</a>” e “IJCIEOM_2020.FS” encontra-se o desenvolvimento da incerteza das medições de vazão de água do CJA-UFSB.</p> <p>4. As planilhas “nhemu_seiqué.MT” e “nhemu_seiqué.FS” são usadas no programa de KALID (2020). Para rodar no programa é necessário renomear para “nhemu_seiqué”.</p> <p> </p> <p>English:</p> <p>Spreadsheets developed for the article entitled “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. He was submitted to the 26th IJCIEOM - International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. In the spreadsheet “Database_IJCIEOM_2020” are all the data used in the research.</p> <p>2. The spreadsheet called “Coverage test” refers to the statistical test done with the average of blocks MT and FS.</p> <p>3. In “IJCIEOM_2020.MT” and “IJCIEOM_2020.FS” there is the development of the uncertainty of water flow measurements from CJA-UFSB.</p> <p>4. The spreadsheets “nhemu_seiqué.MT” and “nhemu_seiqué.FS” are used in the KALID program (2020). To run the program it is necessary to rename it to “nhemu_seiqué”.</p>
Spreadsheets: step by step of data reconciliation
<p>Planilhas desenvolvidas para o artigo intitulado “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. Ele foi submetido no 26th IJCIEOM – International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. Na planilha “Database_IJCIEOM_2020” estão todos os dados usados na pesquisa.</p> <p>2. A planilha denominada “Coverage test” refere-se ao teste estatistico feito com a media dos blocos MT e FS.</p> <p>3. Em “<a href="http://ijcieom_2020.mt/">IJCIEOM_2020.MT</a>” e “IJCIEOM_2020.FS” encontra-se o desenvolvimento da incerteza das medições de vazão de água do CJA-UFSB.</p> <p>4. As planilhas “nhemu_seiqué.MT” e “nhemu_seiqué.FS” são usadas no programa de KALID (2020). Para rodar no programa é necessário renomear para “nhemu_seiqué”.</p> <p> </p> <p>English:</p> <p>Spreadsheets developed for the article entitled “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. He was submitted to the 26th IJCIEOM - International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. In the spreadsheet “Database_IJCIEOM_2020” are all the data used in the research.</p> <p>2. The spreadsheet called “Coverage test” refers to the statistical test done with the average of blocks MT and FS.</p> <p>3. In “IJCIEOM_2020.MT” and “IJCIEOM_2020.FS” there is the development of the uncertainty of water flow measurements from CJA-UFSB.</p> <p>4. The spreadsheets “nhemu_seiqué.MT” and “nhemu_seiqué.FS” are used in the KALID program (2020). To run the program it is necessary to rename it to “nhemu_seiqué”.</p>
Reconciliation of regulatory data: the regulatory networks of Escherichia coli and Bacillus subtilis
<p>The dataset hereby uploaded, presents state-of-art, reconciled transcriptional regulatory networks of <em>Escherichia coli </em>K12 MG1655<em> </em>and <em>Bacillus subtilis </em>str 168<em>. </em>The networks were reconciled through the retrieval and integration of relevant regulatory data from multiple resources, including databases, such as <em>RegulonDB </em>and <em>DBTBS</em> as well as available literature.</p>
Data from: A geography aware reconciliation method to investigate diversification patterns in host/parasite cospeciation interactions
Cospeciation studies aim at investigating whether hosts and symbionts speciate simultaneously or whether the associations diversify through host shifts. This problem is often tackled through reconciliation analyses that map the symbiont phylogeny onto the host phylogeny by mixing different types of diversification events. These reconciliations can be difficult to interpret and not always biologically realistic. Researchers have underlined that the biogeographic histories of both hosts and symbionts influence the probability of cospeciation and host switches, but up to now no reconciliation software integrates geographic data. We present a new functionality in the Mowgli software that bridges this gap. The user can provide geographic information on both the host and symbiont extant and ancestral taxa. Constraints in the reconciliation algorithm have been implemented to generate biologically realistic codiversification scenarios.. We apply our method to the fig/fig wasp association and infer diversification scenarios that differ from reconciliations ignoring geographic information. In addition, we updated the reconciliation viewer SylvX in order to visualize ancestral characters states on the phylogenetic trees and highlight zones that are geographically inconsistent in reconciliations computed without geographic constraintse. We suggest that the comparison of reconciliations obtained with and without geographic constraints can sometimes help solving ambiguities in the biogeographic histories of the partners. With the development of robust methods in historical biogeography and the advent of next-generation sequencing that leads to better-resolved trees, a geography aware reconciliation method represents a substantial advance that is likely to be useful to researchers studying the evolution of biotic interactions and biogeography.
Data from: Seabird and Louse Coevolution: Complex Histories Revealed by 12S rRNA Sequences and Reconciliation Analyses
We investigated the coevolutionary history of seabirds (orders Procellariiformes and Sphenisciformes) and their lice (order Phthiraptera). Independent trees were produced for the seabirds (tree derived from 12S ribosomal RNA (rRNA), isozyme, and behavioral data) and their lice (trees derived from 12S rRNA data). Brookâ s parsimony analysis (BPA) supported a general history of cospeciation (consistency index = 0.84, retention index = 0.81). We inferred that the homoplasy in the BPA was caused by one intrahost speciation, one potential host switching and eight or nine sorting events. Using reconciliation analysis we quantified the cost of fitting the louse tree onto the seabird tree. The reconciled TreeMap tree postulated one host switching, nine cospeciation, three or four intrahost speciation and 11 to 14 sorting events. The number of cospeciation events was significantly more than would be expected due to chance. The sequence data were used to test for rate heterogeneity for both seabirds and lice. The seabird tree showed no significant rate heterogeneity over all of its branches whereas part of the louse tree did show rate heterogeneity. An examination of the codivergent nodes revealed that seabirds and lice have cospeciated synchronously, and that lice have evolved at about 5.5 times the rate of seabirds. Sequence data supported some of the postulated intrahost speciation events (Halipeurus pre-dated the evolution of their present hosts). Sequence data also supported some of the postulated host-switching events. These results demonstrate the value of sequence data and reconciliation analyses in unraveling complex histories between hosts and their parasites.
Data from: Exploring and visualising spaces of tree reconciliations
Tree reconciliation is the mathematical tool that is used to investigate the coevolution of organisms, such as hosts and parasites. A common approach to tree reconciliation involves specifying a model that assigns costs to certain events, such as cospeciation, and then tries to find a mapping between two specified phylogenetic trees which minimises the total cost of the implied events. For such models, it has been shown that there may be a huge number of optimal solutions, or at least solutions that are close to optimal. It is therefore of interest to be able to systematically compare and visualise whole collections of reconciliations between a specified pair of trees. In this paper, we consider various metrics on the set of all possible reconciliations between a pair of trees, some that have been defined before but also new metrics that we shall propose. We show that the diameter for the resulting spaces of reconciliations can in some cases be determined theoretically, information that we use to normalise and compare properties of the metrics. We also implement the metrics and compare their behaviour on several host parasite datasets, including the shapes of their distributions. In addition, we show that in combination with multidimensional scaling, the metrics can be useful for visualising large collections of reconciliations, much in the same way as phylogenetic tree metrics can be used to explore collections of phylogenetic trees. Implementations of the metrics can be downloaded from: https://team.inria.fr/erable/en/team-members/blerina-sinaimeri/reconciliation-distances/
Data from: Seabird and Louse Coevolution: Complex Histories Revealed by 12S rRNA Sequences and Reconciliation Analyses
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Data from: A geography aware reconciliation method to investigate diversification patterns in host/parasite cospeciation interactions
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Data from: Exploring and visualising spaces of tree reconciliations
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Data from: Gene-tree reconciliation with MUL-trees to resolve polyploidy events
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.