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Correction for Patro et al., Shift in Monocyte Apoptosis with Increasing Viral Load and Change in Apoptosis-Related ISG/Bcl2 Family Gene Expression in Chronically HIV-1-Infected Subjects.

Journal of virology

Patro SC, Pal S, Bi Y, Lynn K, Mounzer KC, Kostman JR, Davuluri RV, Montaner LJ.
PMID: 26041838
J Virol. 2015 Jul;89(13):6970. doi: 10.1128/JVI.00735-15.

No abstract available.

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Patro SC, Pal S, Bi Y, et al. Correction for Patro et al., Shift in Monocyte Apoptosis with Increasing Viral Load and Change in Apoptosis-Related ISG/Bcl2 Family Gene Expression in Chronically HIV-1-Infected Subjects. J Virol. 2015;89(13):6970doi: 10.1128/JVI.00735-15.
Patro, S. C., Pal, S., Bi, Y., Lynn, K., Mounzer, K. C., Kostman, J. R., Davuluri, R. V., & Montaner, L. J. (2015). Correction for Patro et al., Shift in Monocyte Apoptosis with Increasing Viral Load and Change in Apoptosis-Related ISG/Bcl2 Family Gene Expression in Chronically HIV-1-Infected Subjects. Journal of virology, 89(13), 6970. https://doi.org/10.1128/JVI.00735-15
Patro, Sean C, et al. "Correction for Patro et al., Shift in Monocyte Apoptosis with Increasing Viral Load and Change in Apoptosis-Related ISG/Bcl2 Family Gene Expression in Chronically HIV-1-Infected Subjects." Journal of virology vol. 89,13 (2015): 6970. doi: https://doi.org/10.1128/JVI.00735-15
Patro SC, Pal S, Bi Y, Lynn K, Mounzer KC, Kostman JR, Davuluri RV, Montaner LJ. Correction for Patro et al., Shift in Monocyte Apoptosis with Increasing Viral Load and Change in Apoptosis-Related ISG/Bcl2 Family Gene Expression in Chronically HIV-1-Infected Subjects. J Virol. 2015 Jul;89(13):6970. doi: 10.1128/JVI.00735-15. PMID: 26041838; PMCID: PMC4468485.
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Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors.

Oncotarget

Malchenko S, Sredni ST, Boyineni J, Bi Y, Margaryan NV, Guda MR, Kostenko Y, Tomita T, Davuluri RV, Velpula K, Hendrix MJC, Soares MB.
PMID: 29568390
Oncotarget. 2018 Feb 09;9(17):13733-13747. doi: 10.18632/oncotarget.24460. eCollection 2018 Mar 02.

CNS Primitive Neuroectodermal tumors (CNS-PNETs) are members of the embryonal family of malignant childhood brain tumors, which remain refractory to current therapeutic treatments. Current paradigm of brain tumorigenesis implicates brain tumor-initiating cells (BTIC) in the onset of tumorigenesis and...

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Malchenko S, Sredni ST, Boyineni J, et al. Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors. Oncotarget. 2018;9(17):13733-13747doi: 10.18632/oncotarget.24460.
Malchenko, S., Sredni, S. T., Boyineni, J., Bi, Y., Margaryan, N. V., Guda, M. R., Kostenko, Y., Tomita, T., Davuluri, R. V., Velpula, K., Hendrix, M. J. C., & Soares, M. B. (2018). Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors. Oncotarget, 9(17), 13733-13747. https://doi.org/10.18632/oncotarget.24460
Malchenko, Sergey, et al. "Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors." Oncotarget vol. 9,17 (2018): 13733-13747. doi: https://doi.org/10.18632/oncotarget.24460
Malchenko S, Sredni ST, Boyineni J, Bi Y, Margaryan NV, Guda MR, Kostenko Y, Tomita T, Davuluri RV, Velpula K, Hendrix MJC, Soares MB. Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors. Oncotarget. 2018 Feb 09;9(17):13733-13747. doi: 10.18632/oncotarget.24460. eCollection 2018 Mar 02. PMID: 29568390; PMCID: PMC5862611.
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ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs.

Bioinformatics (Oxford, England)

Chakraborty A, Ay F, Davuluri RV.
PMID: 34014317
Bioinformatics. 2021 May 20; doi: 10.1093/bioinformatics/btab393. Epub 2021 May 20.

MOTIVATION: Access to large-scale genomics and transcriptomics data from various tissues and cell lines allowed the discovery of wide-spread alternative splicing events and alternative promoter usage in mammalians. Between human and mouse, gene-level orthology is currently present for nearly...

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Chakraborty A, Ay F, Davuluri RV. ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs. Bioinformatics. 2021;doi: 10.1093/bioinformatics/btab393.
Chakraborty, A., Ay, F., & Davuluri, R. V. (2021). ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs. Bioinformatics (Oxford, England), . https://doi.org/10.1093/bioinformatics/btab393
Chakraborty, Abhijit, et al. "ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs." Bioinformatics (Oxford, England) vol. (2021). doi: https://doi.org/10.1093/bioinformatics/btab393
Chakraborty A, Ay F, Davuluri RV. ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs. Bioinformatics. 2021 May 20; doi: 10.1093/bioinformatics/btab393. Epub 2021 May 20. PMID: 34014317; PMCID: PMC8545320.
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Identification of Geographic Specific SARS-Cov-2 Mutations by Random Forest Classification and Variable Selection Methods.

Statistics and applications

Kandpal M, Davuluri RV.
PMID: 32984664
Stat Appl. 2020 Jul;18(1):253-268. Epub 2020 Jun 30.

RNA viral genomes have very high mutations rates. As infection spreads in the host populations, different viral lineages emerge acquiring independent mutations that can lead to varied infection and death rates in different parts of the world. By application...

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Kandpal M, Davuluri RV. Identification of Geographic Specific SARS-Cov-2 Mutations by Random Forest Classification and Variable Selection Methods. Stat Appl. 2020;18(1):253-268
Kandpal, M., & Davuluri, R. V. (2020). Identification of Geographic Specific SARS-Cov-2 Mutations by Random Forest Classification and Variable Selection Methods. Statistics and applications, 18(1), 253-268.
Kandpal, Manoj, and Davuluri, Ramana V. "Identification of Geographic Specific SARS-Cov-2 Mutations by Random Forest Classification and Variable Selection Methods." Statistics and applications vol. 18,1 (2020): 253-268.
Kandpal M, Davuluri RV. Identification of Geographic Specific SARS-Cov-2 Mutations by Random Forest Classification and Variable Selection Methods. Stat Appl. 2020 Jul;18(1):253-268. Epub 2020 Jun 30. PMID: 32984664; PMCID: PMC7514111.
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Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of .

Frontiers in computational neuroscience

Rathore S, Akbari H, Bakas S, Pisapia JM, Shukla G, Rudie JD, Da X, Davuluri RV, Dahmane N, O'Rourke DM, Davatzikos C.
PMID: 31920606
Front Comput Neurosci. 2019 Dec 12;13:81. doi: 10.3389/fncom.2019.00081. eCollection 2019.

Glioblastoma, the most frequent primary malignant brain neoplasm, is genetically diverse and classified into four transcriptomic subtypes, i. e., classical, mesenchymal, proneural, and neural. Currently, detection of transcriptomic subtype is based on

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Rathore S, Akbari H, Bakas S, et al. Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of . Front Comput Neurosci. 2019;13:81doi: 10.3389/fncom.2019.00081.
Rathore, S., Akbari, H., Bakas, S., Pisapia, J. M., Shukla, G., Rudie, J. D., Da, X., Davuluri, R. V., Dahmane, N., O'Rourke, D. M., & Davatzikos, C. (2019). Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of . Frontiers in computational neuroscience, 1381. https://doi.org/10.3389/fncom.2019.00081
Rathore, Saima, et al. "Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of ." Frontiers in computational neuroscience vol. 13 (2019): 81. doi: https://doi.org/10.3389/fncom.2019.00081
Rathore S, Akbari H, Bakas S, Pisapia JM, Shukla G, Rudie JD, Da X, Davuluri RV, Dahmane N, O'Rourke DM, Davatzikos C. Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of . Front Comput Neurosci. 2019 Dec 12;13:81. doi: 10.3389/fncom.2019.00081. eCollection 2019. PMID: 31920606; PMCID: PMC6923885.
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Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis.

Cancer informatics

Shilpi A, Bi Y, Jung S, Patra SK, Davuluri RV.
PMID: 28096648
Cancer Inform. 2017 Jan 09;16:1-13. doi: 10.4137/CIN.S39783. eCollection 2017.

INTRODUCTION: Breast cancer being a multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. However, the task for the identification of these variances is complicated by the interplay between inherited genetic and epigenetic aberrations. Therefore,...

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Shilpi A, Bi Y, Jung S, et al. Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis. Cancer Inform. 2017;16:1-13doi: 10.4137/CIN.S39783.
Shilpi, A., Bi, Y., Jung, S., Patra, S. K., & Davuluri, R. V. (2017). Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis. Cancer informatics, 161-13. https://doi.org/10.4137/CIN.S39783
Shilpi, Arunima, et al. "Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis." Cancer informatics vol. 16 (2017): 1-13. doi: https://doi.org/10.4137/CIN.S39783
Shilpi A, Bi Y, Jung S, Patra SK, Davuluri RV. Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis. Cancer Inform. 2017 Jan 09;16:1-13. doi: 10.4137/CIN.S39783. eCollection 2017. PMID: 28096648; PMCID: PMC5224237.
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Showing 1 to 6 of 6 entries