000 | 01217 a2200349 4500 | ||
---|---|---|---|
005 | 20250517202313.0 | ||
264 | 0 | _c20190513 | |
008 | 201905s 0 0 eng d | ||
022 | _a1098-1004 | ||
024 | 7 |
_a10.1002/humu.23413 _2doi |
|
040 |
_aNLM _beng _cNLM |
||
100 | 1 | _aSaklatvala, Jake R | |
245 | 0 | 0 |
_aText-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients. _h[electronic resource] |
260 |
_bHuman mutation _c05 2018 |
||
300 |
_a643-652 p. _bdigital |
||
500 | _aPublication Type: Journal Article; Research Support, Non-U.S. Gov't | ||
650 | 0 | 4 | _aComputer Simulation |
650 | 0 | 4 | _aData Curation |
650 | 0 | 4 | _aData Mining |
650 | 0 | 4 | _aDatabases, Genetic |
650 | 0 | 4 |
_aDisease _xgenetics |
650 | 0 | 4 | _aGenetic Predisposition to Disease |
650 | 0 | 4 | _aHumans |
650 | 0 | 4 | _aLogistic Models |
650 | 0 | 4 | _aPhenotype |
650 | 0 | 4 | _aProbability |
650 | 0 | 4 | _aSearch Engine |
700 | 1 | _aDand, Nick | |
700 | 1 | _aSimpson, Michael A | |
773 | 0 |
_tHuman mutation _gvol. 39 _gno. 5 _gp. 643-652 |
|
856 | 4 | 0 |
_uhttps://doi.org/10.1002/humu.23413 _zAvailable from publisher's website |
999 |
_c28103088 _d28103088 |