Daniel Tranchina - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 14 from 14

2019

A complete statistical model for calibration of RNA-seq counts using external spike-ins and maximum likelihood theoryRodoniki Athanasiadou, Benjamin Neymotin, Nathan Brandt, Wei Wang, Lionel Christiaen, David Gresham, Daniel Tranchina. ploscb, 15(3), 2019. [doi]

2015

An alternating renewal process describes the buildup of perceptual segregationSara Ashley Steele, Daniel Tranchina, John Rinzel. ficn, 2015:166, 2015. [doi]

2011

A blind sparse deconvolution method for neural spike identificationChaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli. nips 2011: 1440-1448 [doi]

Sparse decomposition of transformation-invariant signals with continuous basis pursuitChaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli. icassp 2011: 4060-4063 [doi]

Recovery of Sparse Translation-Invariant Signals With Continuous Basis PursuitChaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli. tsp, 59(10):4735-4744, 2011. [doi]

2009

A Systems Approach Uncovers Restrictions for Signal Interactions Regulating Genome-wide Responses to Nutritional Cues in ArabidopsisGabriel Krouk, Daniel Tranchina, Laurence Lejay, Alexis A. Cruikshank, Dennis Shasha, Gloria M. Coruzzi, Rodrigo A. Gutiérrez. ploscb, 5(3), 2009. [doi]

Spike Train Statistics and Dynamics with Synaptic Input from any Renewal Process: A Population Density ApproachCheng Ly, Daniel Tranchina. neco, 21(2):360-396, 2009. [doi]

::::In Silico ::::Evaluation of Predicted Regulatory Interactions in ::::Arabidopsis thaliana::::Damion Nero, Manpreet S. Katari, Jonathan Kelfer, Daniel Tranchina, Gloria M. Coruzzi. bmcbi, 10:435, 2009. [doi]

A system biology approach highlights a hormonal enhancer effect on regulation of genes in a nitrate responsive "biomodule"Damion Nero, Gabriel Krouk, Daniel Tranchina, Gloria M. Coruzzi. bmcsb, 3:59, 2009. [doi]

2007

Critical Analysis of Dimension Reduction by a Moment Closure Method in a Population Density Approach to Neural Network ModelingCheng Ly, Daniel Tranchina. neco, 19(8):2032-2092, 2007. [doi]

2001

A population density method for large-scale modeling of neuronal networks with realistic synaptic kineticsE. Haskell, Duane Q. Nykamp, Daniel Tranchina. ijon, 38-40:627-632, 2001. [doi]

A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Extension to Slow Inhibitory SynapsesDuane Q. Nykamp, Daniel Tranchina. neco, 13(3):511-546, 2001.

2000

Fast neural network simulations with population density methodsDuane Q. Nykamp, Daniel Tranchina. ijon, 32-33:487-492, 2000. [doi]

A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientation TuningDuane Q. Nykamp, Daniel Tranchina. jcns, 8(1):19-50, 2000.

Sign in or sign up to see more results.

runs on WebDSL