J. Martini

发表

A review of deep learning applications for genomic selection

P. Pérez-Rodríguez, O. Montesinos-López, A. Montesinos‐López, 2021, BMC Genomics.

Deep Kernel and Deep Learning for Genome-Based Prediction of Single Traits in Multienvironment Breeding Trials

D. Gianola, P. Pérez-Rodríguez, D. Jarquín, 2019, Front. Genet..

Excursions in the Theory of Ligand Binding

J. Martini, 2014 .

Comparison of the kinetics of different Markov models for ligand binding under varying conditions.

M. Habeck, J. Martini, 2015, The Journal of chemical physics.

Approximate Genome-Based Kernel Models for Large Data Sets Including Main Effects and Interactions

P. Pérez-Rodríguez, M. Lillemo, O. Montesinos-López, 2020, Frontiers in Genetics.

Cooperativity, absolute interaction, and algebraic optimization

J. Martini, Nidhi Kaihnsa, Yue Ren, 2019, Journal of Mathematical Biology.

Genomic Prediction Enhanced Sparse Testing for Multi-environment Trials

Y. Beyene, D. Jarquín, Réka Howard, 2020, G3.

Incorporating Gene Annotation into Genomic Prediction of Complex Phenotypes

Zhe Zhang, H. Simianer, N. Gao, 2017, Genetics.

Phantom Epistasis in Genomic Selection: On the Predictive Ability of Epistatic Models

G. de los Campos, H. Simianer, A. Korte, 2020, G3.

Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction.

P. Pérez-Rodríguez, M. Lillemo, D. Jarquín, 2022, Methods in molecular biology.

Accounting for epistasis improves genomic prediction of phenotypes with univariate and bivariate models across environments

H. Simianer, T. Pook, M. Mayer, 2020, Theoretical and Applied Genetics.

On Hadamard and Kronecker products in covariance structures for genotype × environment interaction

J. Martini, J. Crossa, Jaime Cuevas, 2020, The plant genome.

Lost in Translation: On the Problem of Data Coding in Penalized Whole Genome Regression with Interactions

T. Kneib, N. Ha, J. Martini, 2019, G3: Genes, Genomes, Genetics.

On the approximation of interaction effect models by Hadamard powers of the additive genomic relationship.

J. Martini, J. Crossa, F. Toledo, 2020, Theoretical population biology.

Integrating Gene Expression Data Into Genomic Prediction

H. Simianer, N. Gao, J. Martini, 2019, Front. Genet..

Decoupled molecules with binding polynomials of bidegree (n, 2)

J. Martini, Yue Ren, Jacinta Torres, 2017, Journal of mathematical biology.

Editorial: Genomic Selection: Lessons Learned and Perspectives

J. Martini, F. Toledo, V. Wimmer, 2022, Frontiers in Plant Science.

Lost in translation: On the impact of data coding on penalized regression with interactions

T. Kneib, N. Ha, J. Martini, 2018, 1806.03729.

A Model for Carrier-Mediated Biological Signal Transduction Based on Equilibrium Ligand Binding Theory

M. Schlather, J. Martini, Stefan Schütz, 2016, Bulletin of Mathematical Biology.

The effect of the H−1 scaling factors τ and ω on the structure of H in the single-step procedure

H. Simianer, C. Reimer, N. Gao, 2018, Genetics Selection Evolution.

Incorporating Interactions and Gene Annotation Data in Genomic Prediction

Johannes Wolfgang Robert Martini, J. Martini, 2018 .

A Comparison of the Adoption of Genomic Selection Across Different Breeding Institutions

C. Sansaloni, C. Petroli, S. Rensing, 2021, Frontiers in Plant Science.

A Model for Carrier-Mediated Biological Signal Transduction Based on Equilibrium Ligand Binding Theory

Stefan Schütz, Martin Schlather, M. Schlather, 2016, Bulletin of Mathematical Biology.

Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)

Ning Gao, Henner Simianer, Malena Erbe, 2017, BMC Bioinformatics.

Kinetics or Equilibrium? – A Commentary on a Recent Simulation Study of Semiochemical Dose-Response Curves of Insect Olfactory Sensing

M. Habeck, J. Martini, 2014, Journal of Chemical Ecology.

Opportunities and Challenges of Predictive Approaches for Harnessing the Potential of Genetic Resources

J. Martini, J. Crossa, S. Hearne, 2021, Frontiers in Plant Science.

Contrasting biodiversity-ecosystem functioning relationships in phylogenetic and functional diversity.

Bastian Steudel, I. Feussner, C. Hallmann, 2016, The New phytologist.

Epistasis and covariance: how gene interaction translates into genomic relationship

H. Simianer, J. Martini, M. Erbe, 2016, Theoretical and Applied Genetics.

Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)

H. Simianer, N. Gao, J. Martini, 2017, BMC Bioinformatics.

A sufficient condition for penalized polynomial regression to be invariant to translations of the predictor variables

J. Martini, 2020, 2002.04578.

Incorporating Omics Data in Genomic Prediction.

N. Gao, J. Martini, J. Crossa, 2022, Methods in molecular biology.

Cooperative binding: a multiple personality

Michael Habeck, Luis Diambra, M. Habeck, 2015, Journal of Mathematical Biology.

Cooperative binding: a multiple personality

M. Habeck, J. Martini, Luis Diambra, 2015, Journal of Mathematical Biology.

A derivation of the Grand Canonical Partition Function for systems with a finite number of binding sites using a Markov chain model for the dynamics of single molecules

M. Schlather, M. Habeck, J. Martini, 2014, Journal of Mathematical Chemistry.

A mathematical view on the decoupled sites representation

G. Ullmann, J. Martini, J. W. R. Martini, 2013, Journal of mathematical biology.

The meaning of the decoupled sites representation in terms of statistical mechanics and stochastics

G. Matthias Ullmann, Johannes W. R. Martini, Martin Schlather, 2013 .

Decoupled molecules with binding polynomials of bidegree (n, 2)

Yue Ren, Johannes W. R. Martini, Jacinta Torres, 2017, Journal of Mathematical Biology.

A measure to quantify the degree of cooperativity in overall titration curves.

J. Martini, Johannes W R Martini, 2017, Journal of theoretical biology.

On the interaction of two different types of ligands binding to the same molecule part I: basics and the transfer of the decoupled sites representation to systems with n and one binding sites

G. Matthias Ullmann, Johannes W. R. Martini, Martin Schlather, 2013, Journal of Mathematical Chemistry.

On the interaction of different types of ligands binding to the same molecule Part II: systems with n to 2 and n to 3 binding sites

G. Matthias Ullmann, Johannes W. R. Martini, Martin Schlather, 2013, Journal of Mathematical Chemistry.

The effect of the H−1 scaling factors τ and ω on the structure of H in the single-step procedure

H. Simianer, C. Reimer, N. Gao, 2018, Genetics Selection Evolution.

Decoupled molecules with binding polynomials of bidegree (n, 2)

J. Martini, Yue Ren, Jacinta Torres, 2017, Journal of Mathematical Biology.

Epistasis and covariance: how gene interaction translates into genomic relationship

Henner Simianer, Malena Erbe, Johannes W. R. Martini, 2016, Theoretical and Applied Genetics.