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DISPOT: A simple knowledge-based protein domain interaction statistical potential

Oleksandr Narykov, Dmytro Bogatov, Dmitry Korkin
Conference / Journal paper Bioinformatics | 2019 | DOI: 10.1093/bioinformatics/btz587

Abstract

Motivation: The complexity of protein-protein interactions (PPIs) is further compounded by the fact that an average protein consists of two or more domains, structurally and evolutionary independent subunits. Experimental studies have demonstrated that an interaction between a pair of proteins is not carried out by all domains constituting each protein, but rather by a select subset. However, finding which domains from each protein mediate the corresponding PPI is a challenging task.

Results: Here, we present Domain Interaction Statistical POTential (DISPOT), a simple knowledge-based statistical potential that estimates the propensity of an interaction between a pair of protein domains, given their SCOP family annotations. The statistical potential is derived based on the analysis of more than 352,000 structurally resolved protein-protein interactions obtained from DOMMINO, a comprehensive database on structurally resolved macromolecular interactions.

Availability and implementation: DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. The source code for both modes is available on GitHub: github.com/korkinlab/dispot and standalone docker images on DockerHub: hub.docker.com/r/korkinlab/dispot. The web-server is freely available at dispot.korkinlab.org.

Analysis of a Dynamic Voluntary Contribution Mechanism Public Good Game

Dmytro Bogatov
Conference / Journal paper Undergraduate work Issues in Political Economy | 26(1), 116-133, 2017

Abstract

I present a dynamic, voluntary contribution mechanism, public good game and derive its potential outcomes. In each period, players endogenously determine contribution productivity by engaging in costly investment. The level of contribution productivity carries from period to period, creating a dynamic link between periods. The investment mimics investing in the stock of technology for producing public goods such as national defense or a clean environment. After investing, players decide how much of their remaining money to contribute to provision of the public good, as in traditional public good games. I analyze three kinds of outcomes of the game: the lowest payoff outcome, the Nash Equilibria, and socially optimal behavior. In the lowest payoff outcome, all players receive payoffs of zero. Nash Equilibrium occurs when players invest any amount and contribute all or nothing depending on the contribution productivity. Therefore, there are infinitely many Nash Equilibria strategies. Finally, the socially optimal result occurs when players invest everything in early periods, then at some point switch to contributing everything. My goal is to discover and explain this point. I use mathematical analysis and computer simulation to derive the results.

Data MATTERS: Customizing Economic Indices to Measure State Competitiveness

Dmytro Bogatov, Jillian Rose Hennessy
Undergraduate work WPI Library | 2016

Abstract

This project expands the functionality of the Massachusetts Technology, Talent, and Economic Reporting System (MATTERS) for the Massachusetts High Technology Council (MHTC), a protechnology advocacy and lobbyist organization, through the addition of two new features, namely, an Application Program Interface (API) and the Metric Builder. This API defines a communication protocol between MATTERS and other computational-based systems. Extensive API documentation was developed. The Metric Builder is a tool that allows users to create their own indices with custom rules out of existing MATTERS metrics. This empowers them to track individual states' performance using their own custom models.

Investment Trading And Risk Management: Scientifically Developing and Analyzing Trading Systems

Batyrlan Nurbekov, Dmytro Bogatov, Jiacong S Xu, Richard Joseph O'Brien
Undergraduate work WPI Library | 2015

Abstract

The purpose of this IQP project is to scientifically develop profitable systems and indicators for trading in the markets. The project consists of nine individually developed strategies, which were quantitatively analyzed for profitability and then combined into a system of systems. Each individual system or indicator was given defined rules and then allocated simulated money to trade. Two types of systems were mainly developed, predictive and confirmative, leading to a system of systems that incorporated a predictive layer and a confirmative layer in the decision to take positions.