about
Spatial epigenetic control of mono- and bistable gene expressionTransforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola PatientsQuantitative estimation of pesticide-likeness for agrochemical discoveryState-space analysis of time-varying higher-order spike correlation for multiple neural spike train dataMeasuring the Performance of Neural ModelsNeuronal Cell Bodies Remotely Regulate Axonal Growth Response to Localized Netrin-1 Treatment via Second Messenger and DCC DynamicsStability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances.Analyzing spatial data from mouse tracker methodology: An entropic approach.Data-driven significance estimation for precise spike correlationScreenMill: a freely available software suite for growth measurement, analysis and visualization of high-throughput screen data.External and internal constraints on eukaryotic chemotaxis.Southern leaf blight disease severity is correlated with decreased maize leaf epiphytic bacterial species richness and the phyllosphere bacterial diversity decline is enhanced by nitrogen fertilizationSpatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells.Graded defragmentation of cortical neuronal firing during recovery of consciousness in ratsQuantification and classification of neuronal responses in kernel-smoothed peristimulus time histogramsLocal Variation of Hashtag Spike Trains and Popularity in Twitter.Short- and long-latency somatosensory neuronal responses reveal selective brain injury and effect of hypothermia in global hypoxic ischemia.ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike TrainsHelix-Capping Histidines: Diversity of N-H···N Hydrogen Bond Strength Revealed by (2h)JNN Scalar Couplings.Extracting functionally feedforward networks from a population of spiking neurons.Toward Precision Psychiatry: Statistical Platform for the Personalized Characterization of Natural BehaviorsRIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments.Characterization of the Statistical Signatures of Micro-Movements Underlying Natural Gait Patterns in Children with Phelan McDermid Syndrome: Towards Precision-Phenotyping of Behavior in ASD.Characterization of multifocal T2*-weighted MRI hypointensities in the basal ganglia of elderly, community-dwelling subjectsEmergence of event cascades in inhomogeneous networks.The Ca2+-activated Cl- channel TMEM16B regulates action potential firing and axonal targeting in olfactory sensory neurons.Methods for estimating neural firing rates, and their application to brain-machine interfaces.The tubulin repertoire of C. elegans sensory neurons and its context-dependent role in process outgrowth.Single molecule FRET reveals pore size and opening mechanism of a mechano-sensitive ion channel.Information-geometric measures estimate neural interactions during oscillatory brain states.Quantifying the Assembly of Multicomponent Molecular Machines by Single-Molecule Total Internal Reflection Fluorescence MicroscopyRadiomics: a new application from established techniques.Diffusion MRI noise mapping using random matrix theory.Granger causality-based synaptic weights estimation for analyzing neuronal networks.Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacementsNanoparticle Shape Influences the Magnetic Response of Ferro-Colloids.Interspike interval based filtering of directional selective retinal ganglion cells spike trains.Automatically Characterizing Sensory-Motor Patterns Underlying Reach-to-Grasp Movements on a Physical Depth Inversion Illusion.Bursting transition in a linear self-exciting point process.Spinal sensory projection neuron responses to spinal cord stimulation are mediated by circuits beyond gate control.
P2860
Q21090179-AC56871D-4654-4DD0-B681-13A44B671ED5Q27077202-D0C60629-D6B2-45C8-855C-2499287EBF95Q27902266-BF8BC027-802E-4330-B64A-BC04DB30CE8DQ30000858-7D5C5924-1DF0-48FC-A9CD-6BC3484529B2Q30390584-3EB5E295-7E4B-44C2-89E3-20F3DBAB5594Q30833810-B3793CB0-4E16-42CE-96B1-056D99ACF572Q30840648-4A307129-B04C-4CD6-8097-3A73C9D04BE4Q31154307-18FD53BB-8C2F-4FE1-80FC-4A9DE9E42F9EQ33398292-AB42CBA1-BDA5-42DA-9728-E60DB86E40FBQ33618530-41BC783A-CDE0-4AD8-A103-6ED29DDBC8A5Q34006769-FF95FC52-56FF-4EAB-AE35-9D7536C3B878Q34048531-07841A1E-6C5F-447B-B865-9A729D4D3CF7Q34124901-217DC2C7-664B-4D7B-9E85-C8AC217EB8DDQ34194462-A18D2E1B-75CC-447B-9AA2-D9C5B291724EQ35576464-508B2170-32C2-42C8-823E-2EAF7855FCCFQ35687803-7AF3330E-B6B7-4824-B74C-74C7417AD4D3Q35787544-3E919CC0-11BB-4772-9E83-32806193F047Q36078716-ABEB9E71-D5D8-4FD1-A8D0-317825D570B4Q36322226-ECDA6F41-65AF-4F80-B189-FC6EB435E40CQ36332212-85A73322-CC82-48C5-BFB4-630154628F07Q36528552-CECCF90B-EFFA-4E76-8572-EE1B569CC64EQ36783636-1A5D4F51-35C8-41FD-918F-801D582ECE3CQ37039771-E4B2EB8D-E307-4EB3-86FB-EDF250BFEF44Q37180248-6D0EC399-0221-46BA-A161-5E3B616692AFQ37254415-208AC560-C080-4842-9087-003F8BE00BB9Q37285221-60FA6C2F-E118-4089-A6C8-EC6DED381F22Q37435159-0F82F6DE-BD3E-494B-B159-587058D3EA2CQ37518034-6F414DB7-E585-48F6-882F-EC9E41EB5232Q37587497-60ECC361-90CF-44C4-96A4-D635E7DDDD25Q37598865-695639DA-0263-4AC0-8E1A-FEEB27877D87Q38993908-4C1EC753-C0E5-4C99-B832-9108D1FE9EFBQ39044635-67B0CD58-1B13-44FF-9568-76F74B974F0CQ40283062-941E375D-300E-414F-90B3-1E1CA8B4B28FQ41243365-0D894DBA-07BE-4530-91AA-28438920A431Q41353164-45E5E070-E78C-4C4F-8639-442954C0296BQ41519930-7DE59FE8-3137-4E3F-82C2-F4ACA3D69FFAQ42012777-07815B83-AAC0-493D-BB02-CF4F78CC8567Q42120550-F5BAD4E9-121E-4760-9F56-96DA95612846Q42215361-80D3D27D-49F8-4AA1-982C-285DD3F33665Q42225792-E0C2F1C6-5539-4B5F-800D-31EF43715279
P2860
description
2007 nî lūn-bûn
@nan
2007 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2007 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
name
A method for selecting the bin size of a time histogram
@ast
A method for selecting the bin size of a time histogram
@en
A method for selecting the bin size of a time histogram
@nl
type
label
A method for selecting the bin size of a time histogram
@ast
A method for selecting the bin size of a time histogram
@en
A method for selecting the bin size of a time histogram
@nl
prefLabel
A method for selecting the bin size of a time histogram
@ast
A method for selecting the bin size of a time histogram
@en
A method for selecting the bin size of a time histogram
@nl
P3181
P1433
P1476
A method for selecting the bin size of a time histogram
@en
P2093
Shigeru Shinomoto
P304
P3181
P356
10.1162/NECO.2007.19.6.1503
P407
P577
2007-06-01T00:00:00Z