about
Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: synthetic versus real data.Origin of co-expression patterns in E. coli and S. cerevisiae emerging from reverse engineering algorithmsCharacterization of the time course of changes of the evoked electrical activity in a model of a chemically-induced neuronal plasticitymRNA stability and the unfolding of gene expression in the long-period yeast metabolic cycle.Investigating the conformational stability of prion strains through a kinetic replication model.Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbed large-scale biological networks.Predicting and characterizing selective multiple drug treatments for metabolic diseases and cancer.Partial inhibition and bilevel optimization in flux balance analysis.The phototransduction machinery in the rod outer segment has a strong efficacy gradient.Metabolic Adaptation Processes That Converge to Optimal Biomass Flux DistributionsDrug combinatorics and side effect estimation on the signed human drug-target network.The Geometric Phase of Stock Trading.Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis.Qualitative and quantitative responses to press perturbations in ecological networks.Controllability of complex networks with unilateral inputs.Sequential steps underlying neuronal plasticity induced by a transient exposure to gabazine.Common dynamical features of sensory adaptation in photoreceptors and olfactory sensory neurons.A system-level approach for deciphering the transcriptional response to prion infection.Discerning static and causal interactions in genome-wide reverse engineering problems.Decompositions of large-scale biological systems based on dynamical properties.Exploring the low-energy landscape of large-scale signed social networks.Determining the distance to monotonicity of a biological network: a graph-theoretical approach.A kinetic mechanism inducing oscillations in simple chemical reactions networks.Adaptation as a genome-wide autoregulatory principle in the stress response of yeastInvolutive flows and discretization errors for nonlinear driftless control systemsA driver node selection strategy for minimizing the control energy in complex networks 1 1Work supported in part by a grant from the Swedish Research Council (grant n. 2015-04390 to C.A.)Minimum energy control for networks of coupled harmonic oscillators * *Work supported in part by a grant from the Swedish Research Council (grant n. 2015-04390 to C.A.)Stabilization of Stochastic Quantum Dynamics via Open- and Closed-Loop ControlModeling and Control of Quantum Systems: An IntroductionERNEST: a toolbox for chemical reaction network theoryFeedback schemes for radiation damping suppression in NMR: a control-theoretical perspectiveCommuting multiparty quantum observables and local compatibilityCoherent control of open quantum dynamical systemsControllability properties for finite dimensional quantum Markovian master equationsMotion on submanifolds of noninvariant holonomic constraints for a kinematic control system evolving on a matrix Lie groupControllability of quantum mechanical systems by root space decomposition of su(N)Hybrid Control of a Truck and Trailer VehicleThermodynamic model of gene regulation for the Or59b olfactory receptor in Drosophila
P50
Q31111868-03265270-F00B-418C-8436-C477A5A0050EQ33361618-DBFAB430-4543-46E8-8CDE-C1971CB4DED0Q33403392-0F590F7A-F4B7-49E6-B071-4EC076BAEF7FQ33406624-1352EA81-D809-43E7-B517-D2A89A4AABD0Q33478386-E7AA6197-2D00-456A-9E92-2E34AC478A5DQ33600315-D794C472-6F0A-4B34-BDE4-49AFA804616AQ34397561-03381471-98AD-4E25-AFCC-DB719773B9E8Q35055987-F37F7F04-EAF0-4CCB-82A6-EC03127FE569Q35622196-4FE2DFE9-A3E1-4A5E-8FC7-55D371C603B2Q35764740-5BEA6112-664D-4DD2-8BD2-9FE4250E5834Q36104367-CEA611C9-BAF6-4B9B-B372-94A1E6A1A55CQ36111358-F78FC2F6-F5B0-45BA-A806-9435331A5E71Q36180286-9E8A812D-5176-4B7B-860B-29782F12EB47Q41194113-71774082-0DE3-40C1-9B6E-282652BB67B7Q42266202-3C3EF98E-3DC8-40B0-9309-23AD73C1DCA3Q43211960-BC45B7FF-1B5A-4FC6-B1EC-2DD346CF3FBDQ43248945-4E797BC8-4E0A-4B9E-A625-37919FEC2DF5Q44255576-01D78DA3-9F63-4172-B808-2BB445C2F025Q47719303-A6C0BF8A-EE4D-427B-9C73-17EEF458D53CQ48030445-D6007A26-3145-406A-9A77-4021A35FCAB0Q51314973-F24BFA3F-8FC7-41FA-BE56-927624CDFCDFQ51694960-E69B7EE3-FF19-41D3-A996-8A4C65822E01Q51698329-DB84DB54-2DE1-4063-8385-CCFFFAFAD724Q57018745-F00BE32C-BDC0-450C-BE2B-F1A28FBAFFA8Q57084256-F5FF025B-6233-4A1C-BD37-1C7B89E39B50Q57084261-F658F08D-F062-41E8-BA68-C760282F7C0FQ57084266-E28265B0-B491-4E81-965D-4083C2535CC1Q57084315-78D2AAF4-C052-420B-8D5A-1516EFDDD744Q57084324-2E840834-A757-4DD3-93DF-F8007C74BE91Q57084346-29616ED2-6F68-469A-9DB4-559C1BD646E6Q57084348-EFC54DC7-9ACF-40B4-8A93-F8C6C77CF3EEQ57084367-6B8213BE-8A9D-42F8-91D7-88F2D29A183FQ57084371-1F0AD82B-4381-42C7-B2C1-25A1C2177AFCQ57084382-6C29BB6E-C9F2-4D58-ACC7-E6F7ED10342DQ57084387-98B01F94-38F4-41E5-BCA9-4A23BBAD9EC9Q57084389-72046B79-FCC0-480B-AE36-17A4898A6E85Q57084394-3E35F54E-773D-4C94-932C-19E07F589A73Q61814655-5316FBF5-2905-403C-A301-63DC23B8831C
P50
description
hulumtues
@sq
researcher
@en
wetenschapper
@nl
հետազոտող
@hy
name
Claudio Altafini
@ast
Claudio Altafini
@en
Claudio Altafini
@es
Claudio Altafini
@nl
Claudio Altafini
@sl
type
label
Claudio Altafini
@ast
Claudio Altafini
@en
Claudio Altafini
@es
Claudio Altafini
@nl
Claudio Altafini
@sl
prefLabel
Claudio Altafini
@ast
Claudio Altafini
@en
Claudio Altafini
@es
Claudio Altafini
@nl
Claudio Altafini
@sl
P106
P1153
7003915919
P1960
t6F0uycAAAAJ
P21
P2456
P31
P496
0000-0003-4142-6502