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Background Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven mann...
ORGANISM(S): Homo sapiens 
We describe an efficient decision tree searching strategy (DTSS) to boost the identification of cross-linked peptides. The DTSS approach allows the identification of a wealth of complementary information to facilitate the construction of more protein-protein interaction networks for human cell lysat...
ORGANISM(S): Escherichia coli 
2020-11-23 | PXD018291 | Pride
Covalent drug discovery efforts are growing rapidly but have major unaddressed limitations. These include high false positive rates during hit-to-lead identification; the inherent uncoupling of covalent drug concentration and effect [i.e., uncoupling of pharmacokinetics (PK) and pharmacodynamics (PD...
ORGANISM(S): Mus musculus (Mouse) 
2025-01-23 | PXD046903 | Pride

INTRODUCTION: The Metabolomics Standards Initiative has recommended four categories for metabolite assignments in NMR-based metabolic profiling studies. The putatively annotated compound category is most commonly reported by metabolomics investigators. However, there is significa...

2019-09-27 | MTBLS781 | MetaboLights
S. pombe proteome digested separately by four proteases and analyzed with an LTQ-Orbitrap Velos with a data-dependent decision tree method.
2013-12-23 | MSV000078516 | MassIVE
We examined published microarray data from 104 acute lymphoblastic leukaemia patient specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of ge...
ORGANISM(S): Homo sapiens 
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