LRDCs at <i>l</i> = 2 in real networks in Table 2.
<p>Solid squares represent the <i>r</i><sub>2</sub>-values for real-world networks. Open circles denote calculated as the average <i>r</i><sub>2</sub> values over 100 realizations of the corresponding 1-NNCRNs, with error bars indicating the stan...
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2025
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| _version_ | 1852014156413140992 |
|---|---|
| author | Yuka Fujiki (12269596) |
| author2 | Stefan Junk (22793967) |
| author2_role | author |
| author_facet | Yuka Fujiki (12269596) Stefan Junk (22793967) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yuka Fujiki (12269596) Stefan Junk (22793967) |
| dc.date.none.fl_str_mv | 2025-12-05T18:43:38Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0336970.g012 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/LRDCs_at_i_l_i_2_in_real_networks_in_Table_2_/30807216 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cell Biology Neuroscience Biotechnology Evolutionary Biology Developmental Biology Mental Health Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified shortest path length highly assortative power based targeted attacks >< sub >< using two steps power law distributions >- th nearest heterogeneous degree distributions div >< p >< sub xmlns ></ sub two nodes >- nncrns typical cases simulated cases results show random node r </ pearson ’ numerically investigate maximally random law networks l </ hastings algorithm farther scales differs depending degree distribution degree correlations degree correlation degree correlated correlation coefficient adopted poisson |
| dc.title.none.fl_str_mv | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Solid squares represent the <i>r</i><sub>2</sub>-values for real-world networks. Open circles denote calculated as the average <i>r</i><sub>2</sub> values over 100 realizations of the corresponding 1-NNCRNs, with error bars indicating the standard deviation.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_7a3e0a89bc7dc5c8f67c19a1401178ee |
| identifier_str_mv | 10.1371/journal.pone.0336970.g012 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30807216 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | LRDCs at <i>l</i> = 2 in real networks in Table 2.Yuka Fujiki (12269596)Stefan Junk (22793967)Cell BiologyNeuroscienceBiotechnologyEvolutionary BiologyDevelopmental BiologyMental HealthInfectious DiseasesComputational BiologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedPhysical Sciences not elsewhere classifiedshortest path lengthhighly assortative powerbased targeted attacks>< sub ><using two stepspower law distributions>- th nearestheterogeneous degree distributionsdiv >< p>< sub xmlns></ subtwo nodes>- nncrnstypical casessimulated casesresults showrandom noder </pearson ’numerically investigatemaximally randomlaw networksl </hastings algorithmfarther scalesdiffers dependingdegree distributiondegree correlationsdegree correlationdegree correlatedcorrelation coefficientadopted poisson<p>Solid squares represent the <i>r</i><sub>2</sub>-values for real-world networks. Open circles denote calculated as the average <i>r</i><sub>2</sub> values over 100 realizations of the corresponding 1-NNCRNs, with error bars indicating the standard deviation.</p>2025-12-05T18:43:38ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0336970.g012https://figshare.com/articles/figure/LRDCs_at_i_l_i_2_in_real_networks_in_Table_2_/30807216CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/308072162025-12-05T18:43:38Z |
| spellingShingle | LRDCs at <i>l</i> = 2 in real networks in Table 2. Yuka Fujiki (12269596) Cell Biology Neuroscience Biotechnology Evolutionary Biology Developmental Biology Mental Health Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified shortest path length highly assortative power based targeted attacks >< sub >< using two steps power law distributions >- th nearest heterogeneous degree distributions div >< p >< sub xmlns ></ sub two nodes >- nncrns typical cases simulated cases results show random node r </ pearson ’ numerically investigate maximally random law networks l </ hastings algorithm farther scales differs depending degree distribution degree correlations degree correlation degree correlated correlation coefficient adopted poisson |
| status_str | publishedVersion |
| title | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| title_full | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| title_fullStr | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| title_full_unstemmed | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| title_short | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| title_sort | LRDCs at <i>l</i> = 2 in real networks in Table 2. |
| topic | Cell Biology Neuroscience Biotechnology Evolutionary Biology Developmental Biology Mental Health Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified shortest path length highly assortative power based targeted attacks >< sub >< using two steps power law distributions >- th nearest heterogeneous degree distributions div >< p >< sub xmlns ></ sub two nodes >- nncrns typical cases simulated cases results show random node r </ pearson ’ numerically investigate maximally random law networks l </ hastings algorithm farther scales differs depending degree distribution degree correlations degree correlation degree correlated correlation coefficient adopted poisson |