Sergii Domanskyi
Michigan State University
Signal processingFilter (signal processing)ErosionData miningOligonucleotideKineticsDegradation (geology)PolyelectrolyteNanotechnologyChemistryBiological systemApoptosisSoftwareVisualizationComputer scienceChemical engineeringSource codePython (programming language)DiffusionComputational biologyCluster analysisBiologyThermodynamics
40Publications
7H-index
150Citations
Publications 29
Newest
#1Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
#2Alex Hakansson (DI: Discovery Institute)H-Index: 1
Last. Napoleone Ferrara (UCSD: University of California, San Diego)H-Index: 179
view all 7 authors...
VEGF inhibitor drugs have been successful, especially in ophthalmology, but not all patients respond to them. Combinations of drugs are likely to be needed for a really effective therapy of angiogenesis-related diseases. In this paper we describe naturally occurring combinations of receptors in endothelial cells that might help to identify targets for drug combinations. We also develop and share a new computational method and a software tool called DECNEO to identify them. Single-cell gene expre...
Source
#1Minzhang Zheng (MSU: Michigan State University)H-Index: 8
#2Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
Last. George I. Mias (MSU: Michigan State University)H-Index: 11
view all 4 authors...
Temporal behavior is an essential aspect of all biological systems. Time series have been previously represented as networks. Such representations must address two fundamental problems on how to: (1) Create appropriate networks to reflect the characteristics of biological time series. (2) Detect characteristic dynamic patterns or events as network temporal communities. General community detection methods use metrics comparing the connectivity within a community to random models, or are based on ...
2 CitationsSource
#1Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
#2Alex Hakansson (DI: Discovery Institute)H-Index: 1
Last. Carlo Piermarocchi (MSU: Michigan State University)H-Index: 28
view all 5 authors...
Motivation Analysis of singe cell RNA sequencing (scRNA-seq) typically consists of different steps including quality control, batch correction, clustering, cell identification and characterization, and visualization. The amount of scRNA-seq data is growing extremely fast, and novel algorithmic approaches improving these steps are key to extract more biological information. Here, we introduce: (i) two methods for automatic cell type identification (i.e., without expert curator) based on a voting ...
3 CitationsSource
#1George I. Mias (MSU: Michigan State University)H-Index: 11
#2Vikas Vikram Singh (MSU: Michigan State University)H-Index: 7
Last. Jin He (MSU: Michigan State University)H-Index: 4
view all 9 authors...
Saliva omics has immense potential for non-invasive diagnostics, including monitoring very young or elderly populations, or individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over three periods (100 timepoints) involving: (1) hourly sampling over 24 h without intervention, (2) hourly sampling over 24 h including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (3) daily sampling for 33 days profiling t...
1 CitationsSource
#1S. Domanskyi (UCSD: University of California, San Diego)
#1Sergii Domanskyi (UCSD: University of California, San Diego)H-Index: 7
Last. Napoleone Ferrara (UCSD: University of California, San Diego)H-Index: 179
view all 7 authors...
VEGF inhibitor drugs have been successful, especially in ophthalmology, but not all patients respond to them. Combinations of drugs are likely to be needed for a really effective therapy of angiogenesis-related diseases. In this paper we introduce a new concept, the comberon, a term named by analogy with the operon that refers to evolutionarily conserved combinations of co-expressed genes. These genes identify potential drug targets. Our results show that single-cell gene expression data can hel...
Source
#1Carlo Piermarocchi (MSU: Michigan State University)H-Index: 28
#2Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
Last. Giovanni Paternostro (DI: Discovery Institute)H-Index: 20
view all 4 authors...
The Hopfield neural network model is one of the simplest models able to mathematically implement Waddington’s interpretation of normal and anomalous cell phenotypes as dynamical attractors of epigenetic landscapes. Here, we propose a computational approach based on Hopfield’s associative memories that integrate gene expression data and gene interactome networks in (1) a model representing the dynamics and control of disease progression in multiple myeloma (MM), and (2) a model describing the con...
Source
#1Sergii DomanskyiH-Index: 7
#2Carlo PiermarocchiH-Index: 28
Last. George I. Mias (MSU: Michigan State University)H-Index: 11
view all 3 authors...
SUMMARY: PyIOmica is an open-source Python package focusing on integrating longitudinal multiple omics datasets, characterizing and categorizing temporal trends. The package includes multiple bioinformatics tools including data normalization, annotation, categorization, visualization and enrichment analysis for gene ontology terms and pathways. Additionally, the package includes an implementation of visibility graphs to visualize time series as networks. AVAILABILITY AND IMPLEMENTATION: PyIOmica...
7 CitationsSource
#1Minzhang Zheng (MSU: Michigan State University)H-Index: 8
#2Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
Last. George I. Mias (MSU: Michigan State University)H-Index: 11
view all 4 authors...
Motivation: Temporal behavior is an essential aspect of all biological systems. Time series have been previously represented as networks. Such representations must address two fundamental problems: (i) How to create the appropriate network to reflect the characteristics of biological time series. (ii) How to detect characteristic temporal patterns or events as network communities. General methods to detect communities have used metrics to compare the connectivity within a community to the connec...
Source
#1Sergii Domanskyi (Clarkson University)H-Index: 7
#2Dillon T. Gentekos (Cornell University)H-Index: 9
Last. Brett P. Fors (Cornell University)H-Index: 33
view all 4 authors...
Molecular weight distributions (MWD) have a substantial impact on a diverse set of polymer physical and rheological properties, from processability and stiffness to many aspects of block copolymer microphase behavior. The precise MWD compositions of these polymers can be modularly controlled through temporal initiation in anionic polymerizations by metered addition of a discrete initiating species. With the technique described in this work, we identify initiator addition profiles through theoret...
10 CitationsSource
#1Sergii Domanskyi (MSU: Michigan State University)H-Index: 7
#2Alex HakanssonH-Index: 1
Last. Carlo Piermarocchi (MSU: Michigan State University)H-Index: 28
view all 4 authors...
Associative memories in Hopfield's neural networks are mapped to gene expression pattern to model different paths of disease progression towards Multiple Myeloma (MM). The model is built using single cell RNA-seq data from bone marrow aspirates of MM patients as well as patients diagnosed with Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM), two medical conditions that often progress to full MM. Results: We identify different clusters of MGUS, SMM,...
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