scholarly journals Jumper Enables Discontinuous Transcript Assembly in Coronaviruses

2021 ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Hamiltonian Path ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Splice Graph ◽  
Long Read ◽  
Likelihood Model ◽  
Characterization Of Solutions ◽  
Conserved Core ◽  
Transcript Assembly

AbstractGenes in SARS-CoV-2 and, more generally, in viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes, rendering current transcript assembly methods unsuitable to Nidovirales sequencing samples. Here, we introduce the Discontinuous Transcript Assembly problem of finding transcripts and their abundances c given an alignment under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient mixed integer linear program. We show using simulations that our method, Jumper, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1 and SARS-CoV-2 samples, we find that Jumper not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. Jumper enables detailed analyses of Nidovirales transcriptomes.Code availabilitySoftware is available at https://github.com/elkebir-group/Jumper

scholarly journals JUMPER Enables Discontinuous Transcript Assembly in Coronaviruses

2021 ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Hamiltonian Path ◽  
Transcript Level ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Splice Graph ◽  
Long Read ◽  
Likelihood Model ◽  
Characterization Of Solutions ◽  
Transcript Assembly

Abstract Genes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes and produces subgenomic RNAs that express different viral genes. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLY problem of finding transcripts T and their abundances c given an alignment R of paired end short reads under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient progressive heuristic that uses mixed integer linear program. We show using simulations that our method, JUMPER, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.

scholarly journals Jumper enables discontinuous transcript assembly in coronaviruses

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Maximum Likelihood ◽  
Rna Polymerase ◽  
Drug Response ◽  
Transcript Level ◽  
Rna Dependent Rna Polymerase ◽  
Short Read ◽  
Likelihood Model ◽  
Discontinuous Transcription ◽  
Transcript Assembly

AbstractGenes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription which is distinct from alternative splicing in eukaryotes and is mediated by the viral RNA-dependent RNA polymerase. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLYproblem of finding transcripts and their abundances given an alignment of paired-end short reads under a maximum likelihood model that accounts for varying transcript lengths. We show, using simulations, that our method, JUMPER, outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are supported by subsequent orthogonal analyses. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.

scholarly journals Investment Incentives in Competitive Electricity Markets

2018 ◽  
Vol 8 (10) ◽  
pp. 1978 ◽  
Author(s):  
Jaber Valinejad ◽  
Taghi Barforoshi ◽  
Mousa Marzband ◽  
Edris Pouresmaeil ◽  
Radu Godina ◽  
...  
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Planning Horizon ◽  
Optimization Method ◽  
Design Criterion ◽  
Mixed Integer ◽  
Investment Incentives ◽  
Mixed Integer Linear Program ◽  
Interconnected Power System ◽  
The Impact

This paper presents the analysis of a novel framework of study and the impact of different market design criterion for the generation expansion planning (GEP) in competitive electricity market incentives, under variable uncertainties in a single year horizon. As investment incentives conventionally consist of firm contracts and capacity payments, in this study, the electricity generation investment problem is considered from a strategic generation company (GENCO) ′ s perspective, modelled as a bi-level optimization method. The first-level includes decision steps related to investment incentives to maximize the total profit in the planning horizon. The second-level includes optimization steps focusing on maximizing social welfare when the electricity market is regulated for the current horizon. In addition, variable uncertainties, on offering and investment, are modelled using set of different scenarios. The bi-level optimization problem is then converted to a single-level problem and then represented as a mixed integer linear program (MILP) after linearization. The efficiency of the proposed framework is assessed on the MAZANDARAN regional electric company (MREC) transmission network, integral to IRAN interconnected power system for both elastic and inelastic demands. Simulations show the significance of optimizing the firm contract and the capacity payment that encourages the generation investment for peak technology and improves long-term stability of electricity markets.

Optimizing Location and Relocation of Response Units in Guarding Critical Facilities

2005 ◽  
Vol 1923 (1) ◽  
pp. 127-136 ◽  
Author(s):  
Aamod Sathe ◽  
Elise Miller-Hooks
Keyword(s):  
Transportation Network ◽  
Computational Effort ◽  
Optimal Location ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Public And Private ◽  
Emergency Operations ◽  
Response Unit ◽  
Critical Facilities ◽  
Military Units

The ability to locate military units or equipment, police forces, and first responders optimally and to relocate idle units quickly in response to changing conditions is crucial to a country's ability to guard its critical facilities. Such facilities include vital components of the transportation infrastructure, government and monumental buildings, locations of large gatherings, emergency operations centers, and public and private utilities and communications facilities. In this paper, the problem of making optimal location and relocation decisions for a fixed fleet of response units in a transportation network, where travel conditions are uncertain, is addressed. A mixed integer linear program with multiple objectives (maximize secondary coverage and minimize cost) is presented. Because exact solution of such problems may require considerable computational effort, a metaheuristic based on the principles of genetic algorithms is proposed. The heuristic seeks the set of Pareto-optimal location and relocation decisions for each network state. All facilities of concern must be covered by at least one response unit. If the state of the network changes so that coverage is lost (e.g., travel times increase or a response unit is no longer available), one or more of the response units must be relocated. These relocation decisions are also addressed.

scholarly journals Locating Multiple Size and Multiple Type of Charging Station for Battery Electricity Vehicles

2018 ◽  
Vol 10 (9) ◽  
pp. 3267 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Huijie Wen ◽  
Cuiping Zhang
Keyword(s):  
Travel Time ◽  
Electric Vehicles ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Range Limit ◽  
Mixed Integer Linear Program ◽  
Charging Station ◽  
Different Types ◽  
Initial Charge ◽  
Charging Stations

As environmental and energy issues have attracted more and more attention from the public, research on electric vehicles has become extensive and in-depth. As driving range limit is one of the key factors restricting the development of electric vehicles, the energy supply of electric vehicles mainly relies on the building of charging stations, battery swapping stations, and wireless charging lanes. Actually, the latter two kinds of infrastructure are seldom employed due to their immature technology, relatively large construction costs, and difficulty in standardization. Currently, charging stations are widely used since, in the real world, there are different types of charging station with various levels which could be suitable for the needs of network users. In the past, the study of the location charging stations for battery electric vehicles did not take the different sizes and different types into consideration. In fact, it is of great significance to set charging stations with multiple sizes and multiple types to meet the needs of network users. In the paper, we define the model as a location problem in a capacitated network with an agent technique using multiple sizes and multiple types and formulate the model as a 0–1 mixed integer linear program (MILP) to minimize the total trip travel time of all agents. Finally, we demonstrate the model through numerical examples on two networks and make sensitivity analyses on total budget, initial quantity, and the anxious range of agents accordingly. The results show that as the initial charge increases or the budget increases, travel time for all agents can be reduced; a reduction in range anxiety can increase travel time for all agents.

Sign in / Sign up

Export Citation Format

Share Document