Recent Trends in Cancer Genomics and Bioinformatics Tools Development
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References
- Orlov, Y.L.; Baranova, A.V.; Tatarinova, T.V. Bioinformatics Methods in Medical Genetics and Genomics. Int. J. Mol. Sci. 2020, 21, 6224. [Google Scholar] [CrossRef]
- Orlov, Y.; Anashkina, A.; Klimontov, V.; Baranova, A. Medical Genetics, Genomics and Bioinformatics Aid in Understanding Molecular Mechanisms of Human Diseases. Int. J. Mol. Sci. 2021, 22, 9962. [Google Scholar] [CrossRef] [PubMed]
- Orlov, Y.L.; Baranova, A.V.; Markel, A.L. Computational models in genetics at BGRS\SB-2016: Introductory note. BMC Genet. 2016, 17, 155. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Orlov, Y.L.; Hofestädt, R.; Tatarinova, T.V. Bioinformatics research at BGRS\SB-2018. J. Bioinform. Comput. Biol. 2019, 17, 1902001. [Google Scholar] [CrossRef] [PubMed]
- Orlov, Y.L.; Baranova, A.V. Editorial: Bioinformatics of Genome Regulation and Systems Biology. Front. Genet. 2020, 11, 625. [Google Scholar] [CrossRef]
- Baranova, A.V.; Orlov, Y.L. The papers presented at 7th Young Scientists School “Systems Biology and Bioinformatics” (SBB’15): Introductory Note. BMC Genet. 2016, 17, 20. [Google Scholar] [CrossRef] [Green Version]
- Orlov, Y.L.; Galieva, E.R.; Tatarinova, T.V. Bioinformatics research at SBB-2019. BMC Bioinform. 2020, 21 (Suppl. 11), 366. [Google Scholar] [CrossRef]
- Orlov, Y.L.; Voropaeva, E.N.; Chen, M.; Baranova, A.V. Medical genomics at the Systems Biology and Bioinformatics (SBB-2019) school. BMC Med. Genom. 2020, 13 (Suppl. 8), 127. [Google Scholar] [CrossRef]
- Tatarinova, T.V.; Tabikhanova, L.E.; Eslami, G.; Bai, H.; Orlov, Y.L. Genetics research at the “Centenary of human population genetics” conference and SBB-2019. BMC Genet. 2020, 21 (Suppl. 1), 109. [Google Scholar] [CrossRef]
- Tatarinova, T.V.; Baranova, A.V.; Anashkina, A.A.; Orlov, Y.L. Genomics and Systems Biology at the “Century of Human Population Genetics” conference. BMC Genom. 2020, 21 (Suppl. 7), 592. [Google Scholar] [CrossRef]
- Baranova, A.V.; Leberfarb, E.Y.; Lebedev, G.S.; Orlov, Y.L. Medical genetics studies at the SBB-2019 and MGNGS-2019 conferences. BMC Med. Genet. 2020, 21 (Suppl. 1), 186. [Google Scholar] [CrossRef] [PubMed]
- Jung, J.; Hwang, Y.; Ahn, H.; Lee, S.; Yoo, S. Precise Characterization of Genetic Interactions in Cancer via Molecular Network Refining Processes. Int. J. Mol. Sci. 2021, 22, 11114. [Google Scholar] [CrossRef] [PubMed]
- Brito, C.; Costa-Silva, B.; Barral, D.; Pojo, M. Unraveling the Relevance of ARL GTPases in Cutaneous Melanoma Prognosis through Integrated Bioinformatics Analysis. Int. J. Mol. Sci. 2021, 22, 9260. [Google Scholar] [CrossRef] [PubMed]
- Rueda-Martínez, A.; Garitazelaia, A.; Cilleros-Portet, A.; Marí, S.; Arauzo, R.; de Miguel, J.; González-García, B.; Fernandez-Jimenez, N.; Bilbao, J.; García-Santisteban, I. Genetic Contribution of Endometriosis to the Risk of Developing Hormone-Related Cancers. Int. J. Mol. Sci. 2021, 22, 6083. [Google Scholar] [CrossRef] [PubMed]
- Nekrasov, A.; Kozmin, Y.; Kozyrev, S.; Ziganshin, R.; de Brevern, A.; Anashkina, A. Hierarchical Structure of Protein Sequence. Int. J. Mol. Sci. 2021, 22, 8339. [Google Scholar] [CrossRef] [PubMed]
- Savino, A.; Provero, P.; Poli, V. Differential Co-Expression Analyses Allow the Identification of Critical Signalling Pathways Altered during Tumour Transformation and Progression. Int. J. Mol. Sci. 2020, 21, 9461. [Google Scholar] [CrossRef] [PubMed]
- Hemani, G.; Zheng, J.; Elsworth, B.; Wade, K.H.; Haberland, V.; Baird, D.; Laurin, C.; Burgess, S.; Bowden, J.; Langdon, R.; et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018, 7, e34408. [Google Scholar] [CrossRef] [PubMed]
- Nekrasov, A.N.; Alekseeva, L.G.; Pogosyan, R.А.; Dolgikh, D.A.; Kirpichnikov, M.P.; de Brevern, A.G.; Anashkina, A.A. A minimum set of stable blocks for rational design of polypeptide chains. Biochimie 2019, 160, 88–92. [Google Scholar] [CrossRef] [Green Version]
- Karasev, D.; Sobolev, B.; Lagunin, A.; Filimonov, D.; Poroikov, V. Prediction of Protein–ligand Interaction Based on Sequence Similarity and Ligand Structural Features. Int. J. Mol. Sci. 2020, 21, 8152. [Google Scholar] [CrossRef]
- Karasev, D.; Sobolev, B.; Lagunin, A.; Filimonov, D.; Poroikov, V. Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences. Int. J. Mol. Sci. 2020, 21, 24. [Google Scholar] [CrossRef] [Green Version]
- Moldogazieva, N.; Ostroverkhova, D.; Kuzmich, N.; Kadochnikov, V.; Terentiev, A.; Porozov, Y. Elucidating binding sites and affinities of ERα agonists and antagonists to human alpha-fetoprotein by in silico modeling and point mutagenesis. Int. J. Mol. Sci. 2020, 21, 893. [Google Scholar] [CrossRef] [Green Version]
- Snezhkina, A.; Kalinin, D.; Pavlov, V.; Lukyanova, E.; Golovyuk, A.; Fedorova, M.; Pudova, E.; Savvateeva, M.; Stepanov, O.; Poloznikov, A.; et al. Immunohistochemistry and Mutation Analysis of SDHx Genes in Carotid Paragangliomas. Int. J. Mol. Sci. 2020, 21, 6950. [Google Scholar] [CrossRef]
- Snezhkina, A.V.; Fedorova, M.S.; Pavlov, V.S.; Kalinin, D.V.; Golovyuk, A.L.; Pudova, E.A.; Guvatova, Z.G.; Melnikova, N.V.; Dmitriev, A.A.; Razmakhaev, G.S.; et al. Mutation Frequency in Main Susceptibility Genes Among Patients With Head and Neck Paragangliomas. Front. Genet. 2020, 11, 614908. [Google Scholar] [CrossRef] [PubMed]
- Majewska, A.; Budny, B.; Ziemnicka, K.; Ruchała, M.; Wierzbicka, M. Head and Neck Paragangliomas-A Genetic Overview. Int. J. Mol. Sci. 2020, 21, 7669. [Google Scholar] [CrossRef] [PubMed]
- Kudryavtseva, A.V.; Kalinin, D.V.; Pavlov, V.S.; Savvateeva, M.V.; Fedorova, M.S.; Pudova, E.A.; Kobelyatskaya, A.A.; Golovyuk, A.L.; Guvatova, Z.G.; Razmakhaev, G.S.; et al. Mutation profiling in eight cases of vagal paragangliomas. BMC Med. Genom. 2020, 13 (Suppl. 8), 115. [Google Scholar] [CrossRef] [PubMed]
- Chen, M.; Harrison, A.; Shanahan, H.; Orlov, Y. Biological big bytes: Integrative analysis of large biological datasets. J. Integr. Bioinform. 2017, 14, 20170052. [Google Scholar] [CrossRef] [Green Version]
- Tkachev, V.; Sorokin, M.; Borisov, C.; Garazha, A.; Buzdin, A.; Borisov, N. Flexible Data Trimming Improves Performance of Global Machine Learning Methods in Omics-Based Personalized Oncology. Int. J. Mol. Sci. 2020, 21, 713. [Google Scholar] [CrossRef] [Green Version]
- Zolotovskaia, M.; Sorokin, M.; Petrov, I.; Poddubskaya, E.; Moiseev, A.; Sekacheva, M.; Borisov, N.; Tkachev, V.; Garazha, A.; Kaprin, A.; et al. Disparity between Inter-Patient Molecular Heterogeneity and Repertoires of Target Drugs Used for Different Types of Cancer in Clinical Oncology. Int. J. Mol. Sci. 2020, 21, 1580. [Google Scholar] [CrossRef] [Green Version]
- Ermakov, E.; Parshukova, D.; Nevinsky, G.; Buneva, V. Natural Catalytic IgGs Hydrolyzing Histones in Schizophrenia: Are They the Link between Humoral Immunity and Inflammation? Int. J. Mol. Sci. 2020, 21, 7238. [Google Scholar] [CrossRef]
- Nevinsky, G.A.; Baranova, S.V.; Buneva, V.N.; Dmitrenok, P.S. Multiple Sclerosis: Enzymatic Cross Site-Specific Hydrolysis of H1 Histone by IgGs against H1, H2A, H2B, H3, H4 Histones, and Myelin Basic Protein. Biomolecules 2021, 11, 1140. [Google Scholar] [CrossRef]
- Redina, O.; Babenko, V.; Smagin, D.; Kovalenko, I.; Galyamina, A.; Efimov, V.; Kudryavtseva, N. Gene Expression Changes in the Ventral Tegmental Area of Male Mice with Alternative Social Behavior Experience in Chronic Agonistic Interactions. Int. J. Mol. Sci. 2020, 21, 6599. [Google Scholar] [CrossRef]
- Babenko, V.N.; Bragin, A.O.; Spitsina, A.M.; Chadaeva, I.V.; Galieva, E.R.; Orlova, G.V.; Medvedeva, I.V.; Orlov, Y.L. Analysis of differential gene expression by RNA-seq data in brain areas of laboratory animals. J. Integr. Bioinform. 2016, 13, 292. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Smagin, D.A.; Kovalenko, I.L.; Galyamina, A.G.; Orlov, Y.L.; Babenko, V.N.; Kudryavtseva, N.N. Heterogeneity of Brain Ribosomal Genes Expression Following Positive Fighting Experience in Male Mice as Revealed by RNA-Seq. Mol. Neurobiol. 2018, 55, 390–401. [Google Scholar] [CrossRef] [PubMed]
- Bragin, A.O.; Saik, O.V.; Chadaeva, I.V.; Demenkov, P.S.; Markel, A.L.; Orlov, Y.L.; Rogaev, E.I.; Lavrik, I.N.; Ivanisenko, V.A. Role of apoptosis genes in aggression revealed using combined analysis of ANDSystem gene networks, expression and genomic data in grey rats with aggressive behavior. Vavilovskii Zhurnal Genet. I Sel.-Vavilov J. Genet. Breed. 2017, 21, 911–919. [Google Scholar] [CrossRef]
- Ivanisenko, V.A.; Demenkov, P.S.; Ivanisenko, T.V.; Mishchenko, E.L.; Saik, O.V. A new version of the ANDSystem tool for automatic extraction of knowledge from scientific publications with expanded functionality for reconstruction of associative gene networks by considering tissue-specific gene expression. BMC Bioinform. 2019, 20 (Suppl. 1), 34. [Google Scholar] [CrossRef]
- Trifonova, E.; Klimenko, A.; Mustafin, Z.; Lashin, S.; Kochetov, A. The mTOR signaling pathway activity and vitamin D availability control the expression of most autism predisposition genes. Int. J. Mol. Sci. 2019, 20, 6332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Trifonova, E.A.; Klimenko, A.I.; Mustafin, Z.S.; Lashin, S.A.; Kochetov, A.V. Do Autism Spectrum and Autoimmune Disorders Share Predisposition Gene Signature Due to mTOR Signaling Pathway Controlling Expression. Int. J. Mol. Sci. 2021, 22, 5248. [Google Scholar] [CrossRef]
- Ragusa, M.; Santagati, M.; Mirabella, F.; Lauretta, G.; Cirnigliaro, M.; Brex, D.; Barbagallo, C.; Domini, C.; Gulisano, M.; Barone, R.; et al. Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children. Int. J. Mol. Sci. 2020, 21, 6203. [Google Scholar] [CrossRef]
- Saik, O.; Klimontov, V. Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications. Int. J. Mol. Sci. 2020, 21, 8691. [Google Scholar] [CrossRef]
- Klimontov, V.V.; Saik, O.V.; Korbut, A.I. Glucose variability: How Does It Work? Int. J. Mol. Sci. 2021, 22, 7783. [Google Scholar] [CrossRef]
- Donati, S.; Ciuffi, S.; Marini, F.; Palmini, G.; Miglietta, F.; Aurilia, C.; Brandi, M. Multiple Endocrine Neoplasia Type 1: The Potential Role of microRNAs in the Management of the Syndrome. Int. J. Mol. Sci. 2020, 21, 7592. [Google Scholar] [CrossRef] [PubMed]
- Orlov, Y.L.; Tatarinova, T.V.; Anashkina, A.A. Bioinformatics Applications to Reveal Molecular Mechanisms of Gene Expression Regulation in Model Organisms. Int. J. Mol. Sci. 2021, 22, 11973. [Google Scholar] [CrossRef]
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Anashkina, A.A.; Leberfarb, E.Y.; Orlov, Y.L. Recent Trends in Cancer Genomics and Bioinformatics Tools Development. Int. J. Mol. Sci. 2021, 22, 12146. https://doi.org/10.3390/ijms222212146
Anashkina AA, Leberfarb EY, Orlov YL. Recent Trends in Cancer Genomics and Bioinformatics Tools Development. International Journal of Molecular Sciences. 2021; 22(22):12146. https://doi.org/10.3390/ijms222212146
Chicago/Turabian StyleAnashkina, Anastasia A., Elena Y. Leberfarb, and Yuriy L. Orlov. 2021. "Recent Trends in Cancer Genomics and Bioinformatics Tools Development" International Journal of Molecular Sciences 22, no. 22: 12146. https://doi.org/10.3390/ijms222212146