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LitCovid-PubTator

{"project":"LitCovid-PubTator","denotations":[{"id":"209","span":{"begin":1216,"end":1225},"obj":"Disease"}],"attributes":[{"id":"A209","pred":"tao:has_database_id","subj":"209","obj":"MESH:D007239"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Overall network relationship of personal contacts\nIn network analysis, the nodes are individual hosts, and the links between individuals represent interactions that may allow disease transmission. The descriptive statistics demonstrate that the average degree of infectious hosts was 1.117, which was quite low, given that there were 161 other hosts (Table 2). We see that the range of out-degree was significantly larger than that of the in-degree (minimum and maximum), and that there was more variability across the hosts in the out-degree than in the in-degree (standard deviations and variances). The coefficient variations for out-degree and in-degree were 5.87 and 0.47, respectively. Thus, the population was more heterogeneous in structural contact positions with regard to out-degree than with regard to in-degree. The overall centralization of out-degree was high at 46%, and the in-degree centralization was low at 2.4% of these theoretical maximums. We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection6,25,35.\nTable 2 Centrality measure scores and descriptive statistics for the top-5 ranked hosts.\nRank Degree Centrality Betweenness Centrality Closeness Centrality Eigenvector of geodesic distance\nOutDeg Value InDeg Value Bet Value OutFar Value InFar Value Eigen Value\n1 M14 74(45.96) M37 5(3.11) M14 91.75(0.356) M1 314 M162 25119 M14 0.69\n2 M1 31(19.26) M39 M162 4(2.48) M16 25(0.097) M14 10968 M37 25277 M1 0.161\n3 M16 23(14.29) M179 3(1.86) M76 20(0.078) M16 22059 M39 25278 M37 0.111\n4 M76 10(6.21) M10 M40, M46 M65 M67 M74 M107 M164 2(1.24) M15 6(0.023) M76 24472 M179 25280 M39 0.093\n5 M15 6(3.73) M135 4.5(0.017) M15 25116 M164 25441 M76 0.089\nMean 1.117 1.117 1.086 25751.15 25751.15 0.048\nStd. Dev. 6.556 0.526 7.604 2351.923 129.203 0.062\nVariance 42.98 0.276 57.818 5531541.5 16693.4\nMinimum 0 0 0 314 25119\nMaximum 74 5 91.75 26082 26082\nNetwork centralization 45.55% 2.43% 0.35% 47.20% 99.18%"}

LitCovid-PD-MONDO

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T55","span":{"begin":263,"end":273},"obj":"Disease"}],"attributes":[{"id":"A55","pred":"mondo_id","subj":"T55","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"}],"text":"Overall network relationship of personal contacts\nIn network analysis, the nodes are individual hosts, and the links between individuals represent interactions that may allow disease transmission. The descriptive statistics demonstrate that the average degree of infectious hosts was 1.117, which was quite low, given that there were 161 other hosts (Table 2). We see that the range of out-degree was significantly larger than that of the in-degree (minimum and maximum), and that there was more variability across the hosts in the out-degree than in the in-degree (standard deviations and variances). The coefficient variations for out-degree and in-degree were 5.87 and 0.47, respectively. Thus, the population was more heterogeneous in structural contact positions with regard to out-degree than with regard to in-degree. The overall centralization of out-degree was high at 46%, and the in-degree centralization was low at 2.4% of these theoretical maximums. We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection6,25,35.\nTable 2 Centrality measure scores and descriptive statistics for the top-5 ranked hosts.\nRank Degree Centrality Betweenness Centrality Closeness Centrality Eigenvector of geodesic distance\nOutDeg Value InDeg Value Bet Value OutFar Value InFar Value Eigen Value\n1 M14 74(45.96) M37 5(3.11) M14 91.75(0.356) M1 314 M162 25119 M14 0.69\n2 M1 31(19.26) M39 M162 4(2.48) M16 25(0.097) M14 10968 M37 25277 M1 0.161\n3 M16 23(14.29) M179 3(1.86) M76 20(0.078) M16 22059 M39 25278 M37 0.111\n4 M76 10(6.21) M10 M40, M46 M65 M67 M74 M107 M164 2(1.24) M15 6(0.023) M76 24472 M179 25280 M39 0.093\n5 M15 6(3.73) M135 4.5(0.017) M15 25116 M164 25441 M76 0.089\nMean 1.117 1.117 1.086 25751.15 25751.15 0.048\nStd. Dev. 6.556 0.526 7.604 2351.923 129.203 0.062\nVariance 42.98 0.276 57.818 5531541.5 16693.4\nMinimum 0 0 0 314 25119\nMaximum 74 5 91.75 26082 26082\nNetwork centralization 45.55% 2.43% 0.35% 47.20% 99.18%"}

LitCovid-PD-CLO

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T85","span":{"begin":1497,"end":1500},"obj":"http://purl.obolibrary.org/obo/CLO_0007450"},{"id":"T86","span":{"begin":1523,"end":1526},"obj":"http://purl.obolibrary.org/obo/CLO_0007450"},{"id":"T87","span":{"begin":1540,"end":1542},"obj":"http://purl.obolibrary.org/obo/CLO_0007448"},{"id":"T88","span":{"begin":1540,"end":1542},"obj":"http://purl.obolibrary.org/obo/CLO_0050175"},{"id":"T89","span":{"begin":1558,"end":1561},"obj":"http://purl.obolibrary.org/obo/CLO_0007450"},{"id":"T90","span":{"begin":1569,"end":1571},"obj":"http://purl.obolibrary.org/obo/CLO_0007448"},{"id":"T91","span":{"begin":1569,"end":1571},"obj":"http://purl.obolibrary.org/obo/CLO_0050175"},{"id":"T92","span":{"begin":1613,"end":1616},"obj":"http://purl.obolibrary.org/obo/CLO_0007450"},{"id":"T93","span":{"begin":1633,"end":1635},"obj":"http://purl.obolibrary.org/obo/CLO_0007448"},{"id":"T94","span":{"begin":1633,"end":1635},"obj":"http://purl.obolibrary.org/obo/CLO_0050175"},{"id":"T95","span":{"begin":1730,"end":1733},"obj":"http://purl.obolibrary.org/obo/CLO_0050171"},{"id":"T96","span":{"begin":1773,"end":1776},"obj":"http://purl.obolibrary.org/obo/CLO_0007461"},{"id":"T97","span":{"begin":1819,"end":1822},"obj":"http://purl.obolibrary.org/obo/CLO_0007461"},{"id":"T98","span":{"begin":1847,"end":1850},"obj":"http://purl.obolibrary.org/obo/CLO_0007461"}],"text":"Overall network relationship of personal contacts\nIn network analysis, the nodes are individual hosts, and the links between individuals represent interactions that may allow disease transmission. The descriptive statistics demonstrate that the average degree of infectious hosts was 1.117, which was quite low, given that there were 161 other hosts (Table 2). We see that the range of out-degree was significantly larger than that of the in-degree (minimum and maximum), and that there was more variability across the hosts in the out-degree than in the in-degree (standard deviations and variances). The coefficient variations for out-degree and in-degree were 5.87 and 0.47, respectively. Thus, the population was more heterogeneous in structural contact positions with regard to out-degree than with regard to in-degree. The overall centralization of out-degree was high at 46%, and the in-degree centralization was low at 2.4% of these theoretical maximums. We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection6,25,35.\nTable 2 Centrality measure scores and descriptive statistics for the top-5 ranked hosts.\nRank Degree Centrality Betweenness Centrality Closeness Centrality Eigenvector of geodesic distance\nOutDeg Value InDeg Value Bet Value OutFar Value InFar Value Eigen Value\n1 M14 74(45.96) M37 5(3.11) M14 91.75(0.356) M1 314 M162 25119 M14 0.69\n2 M1 31(19.26) M39 M162 4(2.48) M16 25(0.097) M14 10968 M37 25277 M1 0.161\n3 M16 23(14.29) M179 3(1.86) M76 20(0.078) M16 22059 M39 25278 M37 0.111\n4 M76 10(6.21) M10 M40, M46 M65 M67 M74 M107 M164 2(1.24) M15 6(0.023) M76 24472 M179 25280 M39 0.093\n5 M15 6(3.73) M135 4.5(0.017) M15 25116 M164 25441 M76 0.089\nMean 1.117 1.117 1.086 25751.15 25751.15 0.048\nStd. Dev. 6.556 0.526 7.604 2351.923 129.203 0.062\nVariance 42.98 0.276 57.818 5531541.5 16693.4\nMinimum 0 0 0 314 25119\nMaximum 74 5 91.75 26082 26082\nNetwork centralization 45.55% 2.43% 0.35% 47.20% 99.18%"}

LitCovid-PD-CHEBI

LitCovid-sentences

{"project":"LitCovid-sentences","denotations":[{"id":"T120","span":{"begin":0,"end":49},"obj":"Sentence"},{"id":"T121","span":{"begin":50,"end":196},"obj":"Sentence"},{"id":"T122","span":{"begin":197,"end":360},"obj":"Sentence"},{"id":"T123","span":{"begin":361,"end":601},"obj":"Sentence"},{"id":"T124","span":{"begin":602,"end":691},"obj":"Sentence"},{"id":"T125","span":{"begin":692,"end":824},"obj":"Sentence"},{"id":"T126","span":{"begin":825,"end":962},"obj":"Sentence"},{"id":"T127","span":{"begin":963,"end":1115},"obj":"Sentence"},{"id":"T128","span":{"begin":1116,"end":1233},"obj":"Sentence"},{"id":"T129","span":{"begin":1234,"end":1322},"obj":"Sentence"},{"id":"T130","span":{"begin":1323,"end":1422},"obj":"Sentence"},{"id":"T131","span":{"begin":1423,"end":1494},"obj":"Sentence"},{"id":"T132","span":{"begin":1495,"end":1566},"obj":"Sentence"},{"id":"T133","span":{"begin":1567,"end":1641},"obj":"Sentence"},{"id":"T134","span":{"begin":1642,"end":1714},"obj":"Sentence"},{"id":"T135","span":{"begin":1715,"end":1816},"obj":"Sentence"},{"id":"T136","span":{"begin":1817,"end":1877},"obj":"Sentence"},{"id":"T137","span":{"begin":1878,"end":1924},"obj":"Sentence"},{"id":"T138","span":{"begin":1925,"end":1929},"obj":"Sentence"},{"id":"T139","span":{"begin":1930,"end":1934},"obj":"Sentence"},{"id":"T140","span":{"begin":1935,"end":1975},"obj":"Sentence"},{"id":"T141","span":{"begin":1976,"end":2021},"obj":"Sentence"},{"id":"T142","span":{"begin":2022,"end":2045},"obj":"Sentence"},{"id":"T143","span":{"begin":2046,"end":2076},"obj":"Sentence"},{"id":"T144","span":{"begin":2077,"end":2132},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Overall network relationship of personal contacts\nIn network analysis, the nodes are individual hosts, and the links between individuals represent interactions that may allow disease transmission. The descriptive statistics demonstrate that the average degree of infectious hosts was 1.117, which was quite low, given that there were 161 other hosts (Table 2). We see that the range of out-degree was significantly larger than that of the in-degree (minimum and maximum), and that there was more variability across the hosts in the out-degree than in the in-degree (standard deviations and variances). The coefficient variations for out-degree and in-degree were 5.87 and 0.47, respectively. Thus, the population was more heterogeneous in structural contact positions with regard to out-degree than with regard to in-degree. The overall centralization of out-degree was high at 46%, and the in-degree centralization was low at 2.4% of these theoretical maximums. We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection6,25,35.\nTable 2 Centrality measure scores and descriptive statistics for the top-5 ranked hosts.\nRank Degree Centrality Betweenness Centrality Closeness Centrality Eigenvector of geodesic distance\nOutDeg Value InDeg Value Bet Value OutFar Value InFar Value Eigen Value\n1 M14 74(45.96) M37 5(3.11) M14 91.75(0.356) M1 314 M162 25119 M14 0.69\n2 M1 31(19.26) M39 M162 4(2.48) M16 25(0.097) M14 10968 M37 25277 M1 0.161\n3 M16 23(14.29) M179 3(1.86) M76 20(0.078) M16 22059 M39 25278 M37 0.111\n4 M76 10(6.21) M10 M40, M46 M65 M67 M74 M107 M164 2(1.24) M15 6(0.023) M76 24472 M179 25280 M39 0.093\n5 M15 6(3.73) M135 4.5(0.017) M15 25116 M164 25441 M76 0.089\nMean 1.117 1.117 1.086 25751.15 25751.15 0.048\nStd. Dev. 6.556 0.526 7.604 2351.923 129.203 0.062\nVariance 42.98 0.276 57.818 5531541.5 16693.4\nMinimum 0 0 0 314 25119\nMaximum 74 5 91.75 26082 26082\nNetwork centralization 45.55% 2.43% 0.35% 47.20% 99.18%"}

2_test

{"project":"2_test","denotations":[{"id":"32152361-10521342-138518115","span":{"begin":1225,"end":1226},"obj":"10521342"},{"id":"32152361-26883965-138518116","span":{"begin":1227,"end":1229},"obj":"26883965"},{"id":"32152361-751264-138518117","span":{"begin":1230,"end":1232},"obj":"751264"}],"text":"Overall network relationship of personal contacts\nIn network analysis, the nodes are individual hosts, and the links between individuals represent interactions that may allow disease transmission. The descriptive statistics demonstrate that the average degree of infectious hosts was 1.117, which was quite low, given that there were 161 other hosts (Table 2). We see that the range of out-degree was significantly larger than that of the in-degree (minimum and maximum), and that there was more variability across the hosts in the out-degree than in the in-degree (standard deviations and variances). The coefficient variations for out-degree and in-degree were 5.87 and 0.47, respectively. Thus, the population was more heterogeneous in structural contact positions with regard to out-degree than with regard to in-degree. The overall centralization of out-degree was high at 46%, and the in-degree centralization was low at 2.4% of these theoretical maximums. We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection6,25,35.\nTable 2 Centrality measure scores and descriptive statistics for the top-5 ranked hosts.\nRank Degree Centrality Betweenness Centrality Closeness Centrality Eigenvector of geodesic distance\nOutDeg Value InDeg Value Bet Value OutFar Value InFar Value Eigen Value\n1 M14 74(45.96) M37 5(3.11) M14 91.75(0.356) M1 314 M162 25119 M14 0.69\n2 M1 31(19.26) M39 M162 4(2.48) M16 25(0.097) M14 10968 M37 25277 M1 0.161\n3 M16 23(14.29) M179 3(1.86) M76 20(0.078) M16 22059 M39 25278 M37 0.111\n4 M76 10(6.21) M10 M40, M46 M65 M67 M74 M107 M164 2(1.24) M15 6(0.023) M76 24472 M179 25280 M39 0.093\n5 M15 6(3.73) M135 4.5(0.017) M15 25116 M164 25441 M76 0.089\nMean 1.117 1.117 1.086 25751.15 25751.15 0.048\nStd. Dev. 6.556 0.526 7.604 2351.923 129.203 0.062\nVariance 42.98 0.276 57.818 5531541.5 16693.4\nMinimum 0 0 0 314 25119\nMaximum 74 5 91.75 26082 26082\nNetwork centralization 45.55% 2.43% 0.35% 47.20% 99.18%"}