Genome-wide Enhancer Maps Differ Significantly in Genomic Distribution, Evolution, and Function.
ML Benton, SC Talipineni, D Kostka✉, JA Capra✉Preprint (bioRxiv) 2017.
( doi )
Modeling Enhancer-Promoter Interactions with Attention-Based Neural Networks.
W Mao, D Kostka, M Chikina
Preprint (bioRxiv) 2017.
( doi )
Peer reviewed:
Small non-coding RNA expression in developing mouse nephron progenitor cells.
Yu Leng Phua☆, Andrew Clugston☆, Kevin Hong Chen, Dennis Kostka✉, Jacqueline Ho✉Scientific Data (to appear) 2018.
( link to preprint )
Random forest based similarity learning for single cell RNA sequencing data.
M Baran Pouyan and Dennis Kostka
Bioinformatics, 34(13):i79-i88 2018.
( doi )
Developmental loci harbor clusters of accelerated regions that evolved independently in ape lineages.
D Kostka, AK Holloway, KS Pollard
Molecular Biology and Evolution, 35(8):2034-2045 2018.
( doi )
The complex genetics of hypoplastic left heart syndrome.
X Liu, H Yagi, S Saeed, AS Bais, GC Gabriel, Z Chen, KA Peterson, Y Li, MC Schwartz, WT Reynolds, M Saydmohammed, B Gibbs, Y Wu, W Devine, B Chatterjee, NT Klena, D Kostka, KL de Mesy Bentley, MK Ganapathiraju, P Dexheimer, L Leatherbury, O Khalifa, A Bhagat, M Zahid, W Pu, S Watkins, P Grossfeld, S Murray, GA Porter Jr, M Tsang, LJ Martin, DW Benson, BJ Aronow, CW Lo
Nature Genetics 2017, 49(7):1152-1159.
( doi )
DAF-16 and TCER-1 Facilitate Adaptation to Germline Loss by Restoring Lipid Homeostasis and Repressing Reproductive Physiology in C. elegans.
FRG Amrit, EM Steenkiste, R Ratnappan, SW Chen, TB McClendon, D Kostka, J Yanowithz, CP Olsen, A Ghazi
PLoS Genetics 2016, 12(2) e1005788.
( doi )
motifDiverge: a model for assessing the statistical significance of gene regulatory motif divergence between two DNA sequences.
D Kostka, T Friedrich, AK Holloway, KS Pollard
Statistics and Its Interface 2015, 8(4): 463–476.( doi )
Modeling DNA methylation dynamics with approaches from phylogenetics.
JA Capra and D Kostka
Bioinformatics 2014, 30 (17), i408-i414.
( doi )
Gibbon genome and the fast karyotype evolution of small apes.
L Carbone et al. (93 authors)
Nature 2014, 513, 195-201.
( doi )
Integrating diverse datasets improves developmental enhancer prediction.
GD Erwin, N Oksenberg, RM Truty, D Kostka, N Ahituv, K Murphy, KS Pollard and JA Capra
PLoS Computational Biology 2014, 10 (26) , e1003677.
( doi )
miR-17~92 is Required for Nephrogenesis and Renal Function.
AK Marrone, DB Stolz, SI Bastacky, D Kostka, A Bodnar and J Ho
Journal of the American Society of Nephrology (JASN) 2014, 25 (3).
( doi )
A Model-Based Analysis of GC-Biased Gene Conversion in the Human and Chimpanzee Genomes.
JA Capra, MJ Hubisz, D Kostka, KS Pollard and A Siepel
PLoS Genetics 2013, 9 (8), e1003684.
( doi )
The Role of GC-Biased Gene Conversion in Shaping the Fastest Evolving Regions of the Human Genome
D Kostka, MJ Hubisz, A Siepel and KS Pollard
Molecular Biology and Evolution 2012, 29, 1047-1057.
( doi )
A High-Resolution Map of Human Evolutionary Constraint Using 29 Mammals
K Lindblad-Toh et al. (68 authors)
Nature 2011, 478, 476-482.
( doi )
Non-coding sequences near duplicated genes evolve rapidly
D Kostka, MW Hahn and KS Pollard
Genome Biology and Evolution 2010, 2, 518-33.
( doi )
The Importance of Being Cis: Evolution of Orthologous Fish and Mammalian Enhancer Activity
D Ritter, Q Li, D Kostka, KS Pollard, S Guo and JH Chuang
Molecular Biology and Evolution 2010, 27, 2322-2332.
( doi )
Analyzing Gene Perturbation Screens With Nested Effects Models in R and Bioconductor
H Fröhlich, T Beißbarth, A Tresch, D Kostka, J Jacob, R Spang and F Markowetz
Bioinformatics 2008, 24, 2549-2550.
( doi )
Regulatory networks define phenotypic classes of human stem cell lines
FJ Mueller, L Laurent, D Kostka, I Ulitsky, R Williams,
C Lu, MS Rao, R Shamir, PH Schwartz, NO Schmidt and JF Loring
Nature, 2008, 455, 401-105.
( doi )
Computational diagnostics with gene expression profiles
C Lottaz, D Kostka , F Markowetz and R Spang
Methods Mol Biol,
2008, 453, 281-296.
( doi )
Detecting Hierarchical Structure in Molecular Characteristics of Disease Using Transitive
Approximations of Directed Graphs
J Jacob, M Jentsch, D Kostka and R Spang,
Bioinformatics 2008, 24, 995-1001.
( doi )
Microarray Based Diagnosis Profits from Better Documentation of Gene Expression Signatures
D Kostka and R Spang,
PLoS Computational Biology 2008, Feb 15, e22.
( doi )
Nested Effects Models for High-Dimensional Phenotyping Screens
F Markowetz, D Kostka, O Troyanskaya and R Spang,
Bioinformatics 2007, 23, i305-i312.
( doi )
A physical model for tiling array analysis
HR Chung, D Kostka and M Vingron,
Bioinformatics 2007, 23, i80-i86.
( doi )
Patient classification
C Lottaz, D Kostka and R Spang.
In Bioinformatics - From Genomes to Therapies,
T. Lengauer (Ed), Wiley-VCH 2007.
Expression of Late Cell Cycle Genes and an Increased
Proliferative Capacity Characterize Very Early Relapse of Childhood
Acute Lymphoblastic Leukemia
R Kirschner-Schwabe, C Lottaz, J Tödling,
P Rhein, L Karawajew, C Eckert, A von Stackelberg,
U Ungethüm, D Kostka, AE Kulozik,
WD Ludwig, G Henze, R Spang, C Hagemeier and K Seeger,
Clinical Cancer Research 2006, 2(15), 4553-61.
( doi )
Traces of Molecular Disease Mechanisms on Microarrays
D Kostka, C Lottaz and R Spang
In Statistische Methoden in der empirischen Forschung (ISSN 1615-4177),
J. Kaufmann (Hrsg.) Schering AG (Berlin) 2005, 231-236.
Finding Disease Specific Alterations in the Coexpression of Genes
D Kostka and R Spang,
Bioinformatics 2004, 20, i194-i199.
( doi )