Class information for: |
Basic class information |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
10 | 4 | IMMUNOLOGY//TRANSPLANTATION//RHEUMATOLOGY | 1369268 |
244 | 3 | IMMUNOLOGY//PHAGE DISPLAY//BIOSIMILAR | 47231 |
3258 | 2 | ARTIFICIAL IMMUNE SYSTEM//CONCEPTUAL IMMUNOL GRP//NEGATIVE SELECTION ALGORITHM | 2071 |
11402 | 1 | ARTIFICIAL IMMUNE SYSTEM//NEGATIVE SELECTION ALGORITHM//IMMUNE NETWORK | 1011 |
23468 | 1 | CONCEPTUAL IMMUNOL GRP//SELF NONSELF DISCRIMINATION//PAUL EHRLICH | 368 |
29115 | 1 | DENKMALPFLEGE//CD4 LYMPHOCYTE DEPLETION//ADAPTIVE AFFINITY MATURATION | 211 |
32001 | 1 | PRUNUS MUME//MK615//DRUG RAT | 158 |
34953 | 1 | ST PETERSBURG INFORMAT//IMMUNOCOMPUTING//GDELTA GENERATED IDEAL | 118 |
35683 | 1 | SEQUENCE UNIQUENESS//BIOCHEM MOL BIOL ERNESTO QUAGLIARIELLO//SIMILARITY LEVEL | 108 |
36495 | 1 | LIGHT CATALYSIS OXIDATION//3 GORGES ERVOIR REG ECONENVIRONM//AG TIO2 KIT 6 CATALYST | 97 |
Terms with highest relevance score |
rank | Category | termType | chi_square | shrOfCwithTerm | shrOfTermInClass | termInClass |
---|---|---|---|---|---|---|
1 | ARTIFICIAL IMMUNE SYSTEM | authKW | 838759 | 8% | 33% | 169 |
2 | CONCEPTUAL IMMUNOL GRP | address | 508072 | 2% | 90% | 37 |
3 | NEGATIVE SELECTION ALGORITHM | authKW | 285715 | 1% | 72% | 26 |
4 | SELF NONSELF DISCRIMINATION | authKW | 135235 | 1% | 44% | 20 |
5 | IMMUNE NETWORK | authKW | 120705 | 1% | 36% | 22 |
6 | PRUNUS MUME | authKW | 108172 | 1% | 30% | 24 |
7 | SEQUENCE UNIQUENESS | authKW | 106515 | 0% | 100% | 7 |
8 | ARTIFICIAL IMMUNE | authKW | 99587 | 1% | 55% | 12 |
9 | DANGER THEORY | authKW | 96191 | 1% | 45% | 14 |
10 | MK615 | authKW | 93199 | 0% | 88% | 7 |
Web of Science journal categories |
chi_square_rank | Category | chi_square | shrOfCwithTerm | shrOfTermInClass | termInClass |
---|---|---|---|---|---|
1 | Computer Science, Artificial Intelligence | 9229 | 18% | 0% | 371 |
2 | Computer Science, Theory & Methods | 4021 | 13% | 0% | 261 |
3 | Mathematical & Computational Biology | 3476 | 8% | 0% | 162 |
4 | Computer Science, Information Systems | 2265 | 9% | 0% | 190 |
5 | Biology | 1766 | 9% | 0% | 183 |
6 | History & Philosophy of Science | 1685 | 3% | 0% | 67 |
7 | Immunology | 1358 | 14% | 0% | 284 |
8 | Computer Science, Interdisciplinary Applications | 454 | 5% | 0% | 96 |
9 | Computer Science, Cybernetics | 320 | 1% | 0% | 26 |
10 | Spectroscopy | 279 | 4% | 0% | 79 |
Address terms |
chi_square_rank | term | chi_square | shrOfCwithTerm | shrOfTermInClass | termInClass |
---|---|---|---|---|---|
1 | CONCEPTUAL IMMUNOL GRP | 508072 | 2% | 90% | 37 |
2 | BIOCHEM MOL BIOL ERNESTO QUAGLIARIELLO | 84262 | 1% | 46% | 12 |
3 | ST PETERSBURG INFORMAT | 60866 | 0% | 100% | 4 |
4 | DRUG RAT | 49794 | 0% | 55% | 6 |
5 | CARSO CANC | 45649 | 0% | 100% | 3 |
6 | COMP PLICAT M PICONE | 34577 | 0% | 45% | 5 |
7 | HIST MED SOCIAL SCI HUMANISM | 34235 | 0% | 75% | 3 |
8 | HENRY PIERON | 30433 | 0% | 100% | 2 |
9 | INTERDIPARTIMENTALE RIC CANCRO GIORGIO PRODI | 30433 | 0% | 100% | 2 |
10 | L GALVANI INTERDIPARTIMENTAL BIOPHYS | 30433 | 0% | 100% | 2 |
Journals |
chi_square_rank | term | chi_square | shrOfCwithTerm | shrOfTermInClass | termInClass |
---|---|---|---|---|---|
1 | DENKMALPFLEGE | 30425 | 0% | 33% | 6 |
2 | SPECTROSCOPY AND SPECTRAL ANALYSIS | 8208 | 4% | 1% | 76 |
3 | LECTURE NOTES IN COMPUTER SCIENCE | 6743 | 10% | 0% | 202 |
4 | JOURNAL OF THE HISTORY OF BIOLOGY | 4977 | 1% | 2% | 14 |
5 | JOURNAL OF THEORETICAL BIOLOGY | 4531 | 3% | 1% | 58 |
6 | BULLETIN OF MATHEMATICAL BIOLOGY | 4024 | 1% | 1% | 26 |
7 | THEORY IN BIOSCIENCES | 2903 | 0% | 2% | 9 |
8 | APPLIED SOFT COMPUTING | 2117 | 1% | 1% | 24 |
9 | BULLETIN DE LA CLASSE DES SCIENCES ACADEMIE ROYALE DE BELGIQUE | 1837 | 0% | 3% | 4 |
10 | FOLIA BIOLOGICA | 1776 | 1% | 1% | 13 |
Author Key Words |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Classes with closest relation at Level 2 |