about
Cytoscape: a software environment for integrated models of biomolecular interaction networksTools enabling the elucidation of molecular pathways active in human disease: application to Hepatitis C virus infection.Bacterial Internalization, Localization, and Effectors Shape the Epithelial Immune Response during Shigella flexneri InfectionFrom the exposome to mechanistic understanding of chemical-induced adverse effectsAssessing bias in experiment design for large scale mass spectrometry-based quantitative proteomicsAnalysis of time-resolved gene expression measurements across individualsDiscovering regulatory and signalling circuits in molecular interaction networksA network of protein-protein interactions in yeastPredicting protein-peptide interactions via a network-based motif sampler.ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data.Network-based analysis of omics data: the LEAN methodProbIDtree: an automated software program capable of identifying multiple peptides from a single collision-induced dissociation spectrum collected by a tandem mass spectrometer.Alignment of LC-MS images, with applications to biomarker discovery and protein identification.Evolution of metabolic network organization.TLM-Quant: an open-source pipeline for visualization and quantification of gene expression heterogeneity in growing microbial cells.The Cyni framework for network inference in Cytoscape.Filter-free exhaustive odds ratio-based genome-wide interaction approach pinpoints evidence for interaction in the HLA region in psoriasis.Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis.Fragmentation-free LC-MS can identify hundreds of proteins.Identification of additional proteins in differential proteomics using protein interaction networks.Automated flow cytometric analysis across large numbers of samples and cell types.The Cytoscape app article collection.Automated phosphopeptide identification using multiple MS/MS fragmentation modes.The restriction scaffold problem.Network module identification-A widespread theoretical bias and best practices.Detecting multi-way epistasis in family-based association studies.The deferred path heuristic for the generalized tree alignment problem.Algorithms for phylogenetic footprinting.Feature detection with controlled error rates in LC/MS images.Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism.MUDE: a new approach for optimizing sensitivity in the target-decoy search strategy for large-scale peptide/protein identification.Signal maps for mass spectrometry-based comparative proteomics.Towards optimally multiplexed applications of universal arrays.Universal DNA tag systems: a combinatorial design scheme.Common and phylogenetically widespread coding for peptides by bacterial small RNAsMining proteomic data for biomedical researchIndexing and Searching a Mass Spectrometry DatabaseDiscovery of pathways using multiple genome-scale data setsWeighted sequence graphs: boosting iterated dynamic programming using locally suboptimal solutionsTowards optimally multiplexed applications of universal DNA tag systems
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Q24515682-45FC2502-5904-4CAB-B898-09159568926CQ24815400-ED63A8D7-F3AF-4285-8CAF-8FBB5055B2A9Q27322660-97728618-DC6B-4ADF-A3D1-D2333B0528DBQ28078152-71990592-8177-4163-9EBC-308E3527F233Q28235692-FD8BFACC-F8CE-41C2-8042-2F2B42F23E6CQ28536632-9C02F253-976F-4169-B1F2-F77C035F3EA8Q29614951-BBD9A88E-DEB2-438F-BED5-8362D30B400FQ30004209-54A1D1B6-AAF4-4412-A0E9-9522A0DB8BCCQ30163931-E4FFF76C-2291-4326-ADEA-88FD3A2849BAQ30745906-146AF168-B9A7-4629-AAF8-0215753A12E7Q30847234-9EA4BA11-865F-4DA6-8F50-F45E7BC54317Q33224301-5D411A6C-7B5C-46F0-9DAA-39710F685280Q33320987-B49234B2-F51C-487E-8662-9DE7E65F255FQ33575600-32C9D7BE-515E-4D02-B7BC-08BB599DC864Q34850597-541D055D-3526-447C-B5B0-B2F234C95492Q35531204-BBE29CCF-56E4-4BB2-9AC7-A801495F2C31Q35555915-C16A4D51-015A-49D9-933F-C3EB27F398ABQ38327247-53F611F3-6AD8-45C0-95BE-FC9C88AE94C2Q38425732-EDFDE0D3-DF53-4665-A81E-1B8F9E4D20CFQ38463593-073ADF06-0C6B-4882-9B20-5154F8A0EA55Q41597793-80664778-BE49-409D-BF28-71990599E2A2Q41967577-AA386B2E-FB1C-4F40-9A06-A6604C988015Q43741760-5A20EEB0-2CE1-4890-A9E2-A71F0AAE87E8Q47669232-98EDD378-BF18-4922-9807-B4D9C6C40368Q47676365-230F0C3A-2B4F-4656-8A3D-4E0AF41EE920Q47958819-AAB8A79F-6047-4832-B5E6-C045A0693553Q48044958-305A5EBF-BC2C-4227-9785-F93DA46C3D13Q48303804-2D208CA0-9A01-461D-9285-923279D79828Q51403869-1548DBD2-4DA3-47AB-AC3B-2FF42578A2CFQ51411191-08AD16EB-314B-4CDE-B19C-FD56AD3BB533Q51716895-BCD95793-2D92-44AE-B218-79C553BA7BC2Q51960679-36FA418B-5F43-4003-9CC1-772DAF2649F0Q51992773-A0C818D5-DD43-42C2-851E-1D84FBFCACE6Q52070267-097CD9E7-D1AC-41C3-8D51-68AA1D07AA5CQ56881271-804158CF-4FA1-4145-AAF0-D29047404717Q56881273-EDECFFB6-91B4-445E-AA18-C9F7BE9EDF95Q56881275-CCFAB460-CA7C-4FE9-B0F8-9D5B91191564Q56881276-015426D1-E6B2-415D-9EB1-72FE5A400895Q56881278-80B1BF08-A344-4244-B59D-27D8F6C52984Q56881279-F6F5838F-87EA-47F8-B6BB-A24A6215515A
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description
hulumtues
@sq
researcher
@en
ricercatore
@it
wetenschapper
@nl
հետազոտող
@hy
name
Benno Schwikowski
@ast
Benno Schwikowski
@en
Benno Schwikowski
@es
Benno Schwikowski
@nl
Benno Schwikowski
@sl
type
label
Benno Schwikowski
@ast
Benno Schwikowski
@en
Benno Schwikowski
@es
Benno Schwikowski
@nl
Benno Schwikowski
@sl
prefLabel
Benno Schwikowski
@ast
Benno Schwikowski
@en
Benno Schwikowski
@es
Benno Schwikowski
@nl
Benno Schwikowski
@sl
P214
P106
P21
P214
P2456
P31
P496
0000-0001-5127-5619
P7859
lccn-n00000486