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F1000Research|February 7, 2017
Differentially correlated genes in co-expression networks control phenotype transitionsLina D Thomas, Dariia Vyshenska, Natalia Shulzhenko, et al.
Biochemical and Biophysical Research Communications|September 27, 2005
Selection of control genes for quantitative RT-PCR based on microarray dataNatalia Shulzhenko, Anatoly Yambartsev, Amador Goncalves-Primo, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|February 15, 2022
The C-SHIFT Algorithm for Normalizing CovariancesEvgenia Chunikhina, Paul Logan, Yevgeniy Kovchegov, et al.
Bioinformatics and Biology Insights|May 19, 2015
Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for BiologistsXiaoxi Dong, Anatoly Yambartsev, Stephen A Ramsey, et al.
Biology Direct|October 15, 2016
Unexpected links reflect the noise in networksAnatoly Yambartsev, Michael A Perlin, Yevgeniy Kovchegov, et al.
BMC Medical Genomics|October 24, 2020
Noninvasive prenatal paternity determination using microhaplotypes: a pilot studyJaqueline Yu Ting Wang, Martin R Whittle, Renato David Puga, et al.
BMC Bioinformatics|July 16, 2011
Construct and Compare Gene Coexpression Networks with DAPfinder and DAPviewJeff Skinner, Yuri Kotliarov, Sudhir Varma, et al.
Human Molecular Genetics|March 14, 2008
New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancerValeska B Guzman, Anatoly Yambartsev, Amador Goncalves-Primo, et al.
Nature Communications|May 9, 2013
Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancerKarina L Mine, Natalia Shulzhenko, Anatoly Yambartsev, et al.
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