Prati
Mehmet Gültas
Mehmet Gültas
Faculty of Agriculture, South Westphalia University of Applied Sciences
Potvrđena adresa e-pošte na informatik.uni-goettingen.de - Početna stranica
Naslov
Citirano
Citirano
Godina
The synaptic ribbon is critical for sound encoding at high rates and with temporal precision
P Jean, D Lopez de la Morena, S Michanski, LM Jaime Tobón, ...
Elife 7, e29275, 2018
882018
PC-TraFF: identification of potentially collaborating transcription factors using pointwise mutual information
C Meckbach, R Tacke, X Hua, S Waack, E Wingender, M Gültas
BMC bioinformatics 16, 1-21, 2015
272015
CRF-based models of protein surfaces improve protein-protein interaction site predictions
Z Dong, K Wang, TK Linh Dang, M Gültas, M Welter, T Wierschin, ...
BMC bioinformatics 15, 1-14, 2014
242014
The sponge genetree server-providing a phylogenetic backbone for poriferan evolutionary studies
D Erpenbeck, O Voigt, M Gueltas, G Woerheide
Zootaxa 1939 (1), 58–60-58–60, 2008
232008
The sponge genetree server-providing a phylogenetic backbone for poriferan evolutionary studies
D Erpenbeck, O Voigt, M Gueltas, G Woerheide
Zootaxa 1939 (1), 58–60-58–60, 2008
232008
Detecting animal contacts—A deep learning-based pig detection and tracking approach for the quantification of social contacts
M Wutke, F Heinrich, PP Das, A Lange, M Gentz, I Traulsen, FK Warns, ...
Sensors 21 (22), 7512, 2021
212021
Identification of Regulatory SNPs Associated with Vicine and Convicine Content of Vicia faba Based on Genotyping by Sequencing Data Using Deep Learning
F Heinrich, M Wutke, PP Das, M Kamp, M Gültas, W Link, AO Schmitt
Genes 11 (6), 614, 2020
192020
Identification of candidate signature genes and key regulators associated with Trypanotolerance in the Sheko Breed
YA Mekonnen, M Gültas, K Effa, O Hanotte, AO Schmitt
Frontiers in genetics 10, 1095, 2019
192019
Investigation of Pig Activity Based on Video Data and Semi-Supervised Neural Networks
M Wutke, AO Schmitt, I Traulsen, M Gültas
AgriEngineering, 2020
172020
Identification of Age-Specific and Common Key Regulatory Mechanisms Governing Eggshell Strength in Chicken Using Random Forests
F Ramzan, S Klees, AO Schmit, D Cavero, M Gültas
Genes 2020, 11(4), 464; https://doi.org/10.3390/genes11040464, 2020
172020
Computational identification of tissue-specific transcription factor cooperation in ten cattle tissues
L Steuernagel, C Meckbach, F Heinrich, S Zeidler, AO Schmitt, M Gültas
PLOS ONE, 2019
172019
Unravelling the Complex Interplay of Transcription Factors Orchestrating Seed Oil Content in Brassica napus L.
A Rajavel, S Klees, JS Schlüter, H Bertram, K Lu, AO Schmitt, M Gültas
International journal of molecular sciences 22 (3), 1033, 2021
152021
Computational identification of key regulators in two different colorectal cancer cell lines
D Wlochowitz, M Haubrock, J Arackal, A Bleckmann, A Wolff, T Beißbarth, ...
Frontiers in genetics 7, 42, 2016
152016
In Silico Identification of the Complex Interplay between Regulatory SNPs, Transcription Factors, and Their Related Genes in Brassica napus L. Using Multi-Omics Data
S Klees, TM Lange, H Bertram, A Rajavel, JS Schlüter, K Lu, AO Schmitt, ...
International Journal of Molecular Sciences 22 (2), 789, 2021
142021
Combining random forests and a signal detection method leads to the robust detection of genotype-phenotype associations
F Ramzan, M Gültas, H Bertram, D Cavero, AO Schmitt
Genes 11 (8), 892, 2020
142020
Computational detection of stage-specific transcription factor clusters during heart development
S Zeidler, C Meckbach, R Tacke, FS Raad, A Roa, S Uchida, ...
Frontiers in Genetics 7, 33, 2016
142016
Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations
M Gültas, M Haubrock, N Tüysüz, S Waack
BMC bioinformatics 13 (1), 1-12, 2012
122012
Breeding objectives and selection criteria for four strains of Pakistani Beetal goats identified in a participatory approach
F Ramzan, MS Khan, SA Bhatti, M Gültas, AO Schmitt
Small Ruminant Research 190, 106163, 2020
112020
Identifying Cattle Breed-Specific Partner Choice of Transcription Factors during the African Trypanosomiasis Disease Progression Using Bioinformatics Analysis
A Rajavel, F Heinrich, AO Schmit, M Gültas
Vaccines, https://www.mdpi.com/2076-393X/8/2/246, 2020
112020
Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming
M Gültas, G Düzgün, S Herzog, SJ Jäger, C Meckbach, E Wingender, ...
BMC bioinformatics 15 (1), 1-17, 2014
112014
Sustav trenutno ne može provesti ovu radnju. Pokušajte ponovo kasnije.
Članci 1–20