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Article ; Online: Coastal regions in the geography of innovation activity

Mikhaylov Andrey / Mikhaylova Anna / Maksimenko Daniil / Maksimenko Mikhail / Hvaley Dmitry

Geographica Pannonica, Vol 26, Iss 4, Pp 345-

A comparative assessment of marine basins

2022 Volume 355

Abstract: Across the globe marine coasts are experiencing an outstripping growth of the population and economic activity, a phenomenon known as coastalization. Most global cities and industry clusters are located in coastal regions acting as economic growth nodes ... ...

Abstract	Across the globe marine coasts are experiencing an outstripping growth of the population and economic activity, a phenomenon known as coastalization. Most global cities and industry clusters are located in coastal regions acting as economic growth nodes for their respective countries. This divergence is equally true for national innovation systems, gravitating towards highly urbanized coastal areas. The study is designed to evaluate the spatial stratification of the knowledge production between the coastal regions located in different marine basins - Azov-Black, Caspian, Baltic, Arctic, and Pacific. In order to level-out the national differences of the innovation policy and institutional architecture, the research is held in a single country - the Russian Federation. Our research hypothesis suggests that the knowledge production domain of the innovation activity is influenced by urbanization and coastalization, i.e. the proximity to the core city and the coast. We also expect that the coastalization factor would be reflected in intensified involvement of coastal municipalities in knowledge production networks. The study is based on processing the ROSRID database of 66,647 research projects implemented in 2017-2019 and geocoded using the Yandex.Maps API. The research has shown that the urbanization factor has the strongest influence in configuration of R&D networks - the core centers of knowledge production are the largest cities in marine basins that give further impetus to the involvement of neighboring municipalities. Nearly 70% of municipalities across marine basins have limited or no involvement in the knowledge production, except the Baltic and Azov-Black Sea basins that feature the strongest performance. Overall, the proximity to the coast of non-freezing seas has a positive correlation with the number of R&Ds executed and funded. Considering the research topics, the share of marine-related research is typically funded by coastal regions, whereas the executed R&Ds cover a broad variety of ...
Keywords	geography of innovation ; knowledge distribution ; knowledge production ; national innovation system ; coastal regions ; Geography (General) ; G1-922
Subject code	910
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	University of Novi Sad, Department of Geography, Tourism and Hotel Management
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Accuracy of Gene Expression Prediction From Genotype Data With PrediXcan Varies Across and Within Continental Populations.

Mikhaylova, Anna V / Thornton, Timothy A

Frontiers in genetics

2019 Volume 10, Page(s) 261

Abstract: Using genetic data to predict gene expression has garnered significant attention in recent years. PrediXcan has become one of the most widely used gene-based methods for testing associations between predicted gene expression values and a phenotype, which ...

Abstract	Using genetic data to predict gene expression has garnered significant attention in recent years. PrediXcan has become one of the most widely used gene-based methods for testing associations between predicted gene expression values and a phenotype, which has facilitated novel insights into the relationship between complex traits and the component of gene expression that can be attributed to genetic variation. The gene expression prediction models for PrediXcan were developed using supervised machine learning methods and training data from the Depression Genes and Networks (DGN) study and the Genotype-Tissue Expression (GTEx) project, where the majority of subjects are of European descent. Many genetic studies, however, include samples from multi-ethnic populations, and in this paper we evaluate the accuracy of PrediXcan for predicting gene expression in diverse populations. Using transcriptomic data from the GEUVADIS (Genetic European Variation in Disease) RNA sequencing project and whole genome sequencing data from the 1000 Genomes project, we evaluate and compare the predictive performance of PrediXcan in an African population (Yoruban) and four European ancestry populations for thousands of genes. We evaluate a range of models from the PrediXcan weight databases and use Pearson's correlation coefficient to assess gene expression prediction accuracy with PrediXcan. From our evaluation, we find that the predictive performance of PrediXcan varies substantially among populations from different continents (
Language	English
Publishing date	2019-04-03
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2019.00261
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Remote-sensing technology in mapping socio-economic divergence of Europe

Mikhaylov Andrey / Mikhaylova Anna / Alsynbaev Kamil / Bryksin Vitaliy / Hvaley Dmitry

Bulletin of Geography: Socio-Economic Series, Vol 52, Iss 52, Pp 69-

2021 Volume 84

Abstract: Marine and ocean coasts traditionally act as natural growth poles for humankind. Recent studies conducted by scholars from both natural and social sciences suggest that coastal zones accumulate population, agglomerate industries, attract entrepreneurs, ... ...

Abstract	Marine and ocean coasts traditionally act as natural growth poles for humankind. Recent studies conducted by scholars from both natural and social sciences suggest that coastal zones accumulate population, agglomerate industries, attract entrepreneurs, and pull investments. The coastalisation effect remains one of the defining factors of regional development around the globe and is projected to strengthen over the next quarter century. Deepening socio-economic inequality and polarisation between countries and regions despite efforts taken with convergence policies put the “marine factor” on the research agenda. The study contains a comparative evaluation of coastalisation processes across the regions of Europe using remote-sensing technology and statistical multivariate analysis for testing the correlation level of results. The research is based on a dataset for 413 regions of Europe featuring indicators for population density and Gross Regional Product (GRP) in Purchasing Power Parity (PPP) per sq. km. The regions are grouped into clusters depending on their socio-economic indicators and the intensity of nocturnal illumination. The results suggest that coastal and inland region types evenly distribute between clusters, with an average of 40% coastal. Observations of nocturnal illumination clearly indicate an extensive anthropogenic impact on European coasts, both northern and southern. However, their overall luminosity is inferior to inland territories. The study concludes with four patterns derived from a combined methodology of socio-economic indicators and remote-sensing of night-time lighting.
Keywords	coastal region ; coastalisation ; regional divergence ; polarisation ; nocturnal illumination ; remote sensing ; Geography (General) ; G1-922
Subject code	910
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	Sciendo
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: State management of labor migration (as exemplified by the Sakha Republic [Yakutia])

Mikhaylova, Anna

International journal of economics and financial issues : IJEFI Vol. 6, No. 8 , p. 346-353

2016 Volume 6, Issue 8, Page(s) 346–353

Author's details	Anna Mikhaylova
Keywords	Labor Migration ; State Regulation ; International Labor Migration ; Regional Labor Market ; Development
Language	English
Size	Online-Ressource
Publisher	EconJournals
Publishing place	Mersin
Document type	Article ; Online
ZDB-ID	2632572-X
ISSN	2146-4138
ISSN	2146-4138
Database	ECONomics Information System

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Article ; Online: Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia.

Mikhaylova, Anna A / Mikhaylov, Andrey S / Savchina, Oksana V

Data in brief

2019 Volume 27, Page(s) 104640

Abstract: This article presents regional-level data that can be used for comparative territorial studies on innovation dynamics. The dataset covers a series of 50 indicators grouped into a matrix of 5 elements of regional innovation system (human resources - HR, ... ...

Abstract	This article presents regional-level data that can be used for comparative territorial studies on innovation dynamics. The dataset covers a series of 50 indicators grouped into a matrix of 5 elements of regional innovation system (human resources - HR, infrastructure, research & development sector - R&D, innovative milieu, framework conditions) and 5 components of innovation security (economic, scientific and technological - S&T, social, political, geo-ecological). This complex set of interrelated data enables to grasp the catalyst and inhibitor factors that have a significant impact on the sustainable development of a particular regional innovation system. The innovation security approach used enables to consider the locus of innovation processes, account for the relationship between individual components of regional innovation systems and acknowledge for the unique properties of the regions. The database includes statistics for a total set of 85 regions of the Russian Federation over a period of 2015 and 2016. Spatial differentiation is made on to coastal and inland regions. This enables to identify the development patterns as influenced by the global trend of coastalization.
Language	English
Publishing date	2019-10-14
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409 ; 2352-3409
ISSN (online)	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2019.104640
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.

Wittich, Henry / Ardlie, Kristin / Taylor, Kent D / Durda, Peter / Liu, Yongmei / Mikhaylova, Anna / Gignoux, Chris R / Cho, Michael H / Rich, Stephen S / Rotter, Jerome I / Manichaikul, Ani / Im, Hae Kyung / Wheeler, Heather E

American journal of human genetics

2024 Volume 111, Issue 3, Page(s) 445–455

Abstract: Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start ... ...

Abstract	Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π
MeSH term(s)	Humans ; Transcriptome/genetics ; Proteome/genetics ; Multifactorial Inheritance ; Quantitative Trait Loci/genetics ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide/genetics
Chemical Substances	Proteome
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	219384-x
ISSN	1537-6605 ; 0002-9297
ISSN (online)	1537-6605
ISSN	0002-9297
DOI	10.1016/j.ajhg.2024.01.006
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Geospatial dataset for analyzing socio-economic regional divergence of European regions.

Mikhaylov, Andrey S / Mikhaylova, Anna A / Kuznetsova, Tatyana Yu

Data in brief

2018 Volume 19, Page(s) 2374–2383

Abstract: This data article presents macroeconomic data that can be used for comparative territorial studies. The data cover a sample of 413 regions (national administrative-territorial units corresponding to second level of a common classification of territorial ... ...

Abstract	This data article presents macroeconomic data that can be used for comparative territorial studies. The data cover a sample of 413 regions (national administrative-territorial units corresponding to second level of a common classification of territorial units for statistics of the European Commission - NUTS 2 level region of the European Union, and comparable administrative-territorial units outside the EU) of 48 European countries, including Cyprus, Turkey, the European part of Russia, and two partially recognized states - the Republic of Kosovo and the Pridnestrovian Moldavian Republic. The statistical database covers a five-year period of 2010-2014. This dataset is created to enhance our understanding of the contemporary coastalization dynamics in Europe. Despite the fact that coastal regions of European countries exhibit an extensive level of development and remain attractive to human settlement, industry localization, and investment flows their contribution to the socio-economic development of Europe is unclear. The reported data cover a series of macroeconomic data on key indicators traditionally used in comparative analysis of regional development: average annual population, gross regional product (GRP) in purchasing power parity (PPP), labor productivity, population density and GRP (PPP) values per sq.km. Accounting for differences in geoeconomic position of the European regions enables to distinguish four subtypes of regions with a particular emphasis on the coastal area: coastal border, coastal other, coastal hinterland, and inland other. An additional focus is made on differentiating the performance indicators of regions depending on their border geo-economic position: border regions with a state border over land, lake or river surface, and midland regions - other non-border regions. This data is to be used as a comparative benchmark for the coastal border subgroup of regions against the totality of border and midland regions.
Language	English
Publishing date	2018-07-19
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2018.07.027
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI.

Sun, Quan / Rowland, Bryce T / Chen, Jiawen / Mikhaylova, Anna V / Avery, Christy / Peters, Ulrike / Lundin, Jessica / Matise, Tara / Buyske, Steve / Tao, Ran / Mathias, Rasika A / Reiner, Alexander P / Auer, Paul L / Cox, Nancy J / Kooperberg, Charles / Thornton, Timothy A / Raffield, Laura M / Li, Yun

Nature communications

2024 Volume 15, Issue 1, Page(s) 1016

Abstract: Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for ... ...

Abstract	Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
MeSH term(s)	Humans ; Black or African American/genetics ; Computer Simulation ; Genetic Predisposition to Disease ; Genome, Human ; Genome-Wide Association Study/methods ; Phenotype ; Risk Factors ; Software ; Genetic Risk Score
Language	English
Publishing date	2024-02-03
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-45135-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Fiscal resilience of Russia's regions in the face of COVID-19

Klimanov, Vladimir / Kazakova, Sofia / Mikhaylova, Anna / Safina, Aliya

Journal of Public Budgeting, Accounting & Financial Management

2020 Volume ahead-of-print, Issue ahead-of-print

Abstract: Purpose The purpose of the study was to analyze how COVID-19 pandemic affects regional budgets and regional fiscal resilience in Russia. Design/methodology/approach The research article is structured as follows. Based on the official data from the ... ...

Abstract	Purpose The purpose of the study was to analyze how COVID-19 pandemic affects regional budgets and regional fiscal resilience in Russia. Design/methodology/approach The research article is structured as follows. Based on the official data from the Ministry of Finance, the Federal Treasure and the Accounts Chamber of the Russian Federation, first, the state of Russian regional budgets before and under COVID-19 is analyzed. Second, due to the increase of regional spending commitments under pandemic the regional debt dependence is reviewed. Third, anticrisis fiscal measures which have been taken to combat the negative impact of COVID-19 are discussed. Findings In general, 2020 may be the most difficult for regional budgets, although the results of the first quarter do not show such tension. However, the impact of COVID-19 on budget indicators is ambiguous because the economic crisis of 2020 is dual, including the crisis in the oil markets. The pandemic has become a unique global phenomenon, the effect of which is difficult to identify and interpret outside of the economic aspects of life. Originality/value The value of the article is based on the overview of the state of regional budgets before and under COVID-19, on the analysis of how pandemic affects fiscal resilience of the regional budgets and on the forecast of how serious the volume of lost revenues are going to be.
Keywords	Strategy and Management ; Public Administration ; covid19
Language	English
Publisher	Emerald
Publishing country	uk
Document type	Article ; Online
ZDB-ID	2070463-X
ISSN	1945-1814 ; 1096-3367
ISSN (online)	1945-1814
ISSN	1096-3367
DOI	10.1108/jpbafm-07-2020-0123
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Coastal Countryside Innovation Dynamics in North-Western Russia

Mikhaylov Andrey S. / Mikhaylova Anna A. / Lachininskii Stanislav S. / Hvaley Dmitry V.

European Countryside, Vol 11, Iss 4, Pp 541-

2019 Volume 562

Abstract: Coastal regions are generally conceived as highly advanced in terms of socioeconomic and innovative development. Acting as international contact zones, coastal agglomerations are described as gateways for absorbing new knowledge, technologies, business ... ...

Abstract	Coastal regions are generally conceived as highly advanced in terms of socioeconomic and innovative development. Acting as international contact zones, coastal agglomerations are described as gateways for absorbing new knowledge, technologies, business cultures, etc. Yet, this perception is based on studies of large coastal cities and agglomerations. In our study, we focus on coastalization effects manifested in rural settlements and evaluate the innovation capability of the economies of coastal rural areas. The research scope covers 13 municipalities of the Leningrad region, including 134 rural settlements. The research methodology is structured into three main blocks: the evaluation of the human capital, assessment of the favorability of the entrepreneurial environment, and analysis of susceptibility of local economies to innovations. The list of analyzed innovation dynamics parameters includes the geospatial data for the distribution of population, companies and individual entrepreneurs, localization of specialized support and innovation infrastructure, sectoral analysis of the economic structure, digitalization aspects, et cetera. The data coverage period is 2010–2019 with variations depending on the availability of individual indicators. The research findings reveal particular features of the countryside as compared to urban settlements. Strong asymmetries are observed between the development of rural settlements cross-influenced by coastalization, near-metropolitan location, and national border proximity.
Keywords	innovation dynamics ; coastal countryside ; suburbanization ; coastal region ; leningrad region ; russia ; Agriculture ; S ; Social Sciences ; H
Subject code	910
Language	English
Publishing date	2019-12-01T00:00:00Z
Publisher	Sciendo
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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