Combinatorial algorithms for the generalized circulation problem

Goldberg, Andrew V.; Plotkin, Serge; Tardos, Éva

doi:10.1109/sfcs.1988.21959

Cited by 24 publications

(33 citation statements)

References 23 publications

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“…The maximum generalized flow problem is a special case of linear programming, and it can be solved by general-purpose linear programming techniques such as the primal simplex method 33 . Several combinatorial methods that solve the program in polynomial time are also described in the literature 34 .…”

Section: Methodsmentioning

confidence: 99%

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

et al. 2015

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Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.

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Section: Methodsmentioning

confidence: 99%

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

et al. 2015

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“…A weakly polynomial algorithm for this problem can be found in [GoPT91]. This may serve as a model for exchanging currencies 15 , or for losses in a water supply system due to evaporation.…”

Section: Some Further Problemsmentioning

confidence: 99%

Graphs, Networks and Algorithms

Jungnickel

2008

Algorithms and Computation in Mathematics

239

122

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“…A polynomial algorithm for this problem was proposed by Wayne in [51]. Goldberg et al presented combinatorial algorithms for the Generalized Circulation Problem in [19]. The generalized network flows were also discussed by Cohen and Megiddo [13] and Glover et al in [18].…”

Section: Introductionmentioning

confidence: 99%

The Nonlinear Generalized Transportation Problem with convex costs

Anholcer

2015

Croat. Oper. Res. Rev.

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Abstract. We investigate the Nonlinear Generalized Transportation Problem (NGTP), where the transportation costs and the costs that depend on the amount of good delivered to the destination points are strictly convex functions. The amounts of goods change during the transportation process. This model may correspond, for example, with a congested network where the time costs are involved. First, we present the NGTIP model, then provide a method of solving the problems of this type and then we prove convergence of the method. The numerical experiments prove the effectiveness of the presented algorithm.

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Combinatorial algorithms for the generalized circulation problem

Cited by 24 publications

References 23 publications

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

Graphs, Networks and Algorithms

The Nonlinear Generalized Transportation Problem with convex costs

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