16 papers · ranked by Valyu relevance
Peter Steffen, Robert Giegerich
Background Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to…
Mateusz Gruzewski, Marek Palkowski, Ramon Antonio Rodriges Zalipynis
In this article, we present an efficient and concise OpenMP implementation of the Nussinov RNA folding algorithm, a well-known representative of non-serial polyadic dynamic programming (NPDP). Our goal is to develop an optimized implementation that can serve as a template for related dynamic programming applications.…
Kathrin Ungru, Xiaoyi Jiang
Many applications in biomedical imaging have a demand on automatic detection of lines, contours, or boundaries of bones, organs, vessels, and cells. Aim is to support expert decisions in interactive applications or to include it as part of a processing pipeline for automatic image analysis. Biomedical images often…
Christian Höner zu Siederdissen, Sonja J Prohaska, Peter F Stadler
Background Dynamic programming algorithms provide exact solutions to many problems in computational biology, such as sequence alignment, RNA folding, hidden Markov models (HMMs), and scoring of phylogenetic trees. Structurally analogous algorithms compute optimal solutions, evaluate score distributions, and perform…
Georg Sauthoff, Mathias Möhl, Stefan Janssen, Robert Giegerich
Motivation: Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman’s GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique.…
Fereshteh Vaezi Jezeie, Seyed Jafar Sadjadi, Ahmad Makui, Seyedali Mirjalili
'Seyedali Mirjalili'] Portfolio optimization is one of the most important issues in financial markets. In this regard, the more realistic are assumptions and conditions of modelling to portfolio optimization into financial markets, the more reliable results will be obtained. This paper studies the knapsack-based…
Ken D Nguyen, Yi Pan, Ge Nong
Background One of the most fundamental and challenging tasks in bio-informatics is to identify related sequences and their hidden biological significance. The most popular and proven best practice method to accomplish this task is aligning multiple sequences together. However, multiple sequence alignment is a computing…
Dimitris Papamichail, Georgios Papamichail
Background The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variants of the problem, including comparison of two strings, approximate…
Yelena Frid, Dan Gusfield
Background The problem of computationally predicting the secondary structure (or folding) of RNA molecules was first introduced more than thirty years ago and yet continues to be an area of active research and development. The basic RNA-folding problem of finding a maximum cardinality, non-crossing, matching of…
Yohei M. Rosen, Benedict J. Paten
Background Hidden Markov models of haplotype inheritance such as the Li and Stephens model allow for computationally tractable probability calculations using the forward algorithm as long as the representative reference panel used in the model is sufficiently small. Specifically, the monoploid Li and Stephens model and…
Maciej Nowak, Tadeusz Trzaskalik, Sebastian Sitarz, Ewa Roszkowska + 1 more
'Marek Szopa'] A problem that appears in many decision models is that of the simultaneous occurrence of deterministic, stochastic, and fuzzy values in the set of multidimensional evaluations. Such problems will be called mixed problems. They lead to the formulation of optimization problems in ordered structures and…
Jose Barambones, Ricardo Imbert, Cristian Moral, Claudio Savaglio + 1 more
'Reza Malekian'] Context: At present, sensor-based systems are widely used to solve distributed problems in changing environments where sensors are controlled by intelligent agents. On Multi-Agent Systems, agents perceive their environment through such sensors, acting upon that environment through actuators in a…
Jordan Moutet, Eric Rivals, Fabio Pardi, Mingfu Shao
Ancestral sequence reconstruction is an important task in bioinformatics, with applications ranging from protein engineering to the study of genome evolution. When sequences can only undergo substitutions, optimal reconstructions can be efficiently computed using well-known algorithms. However, accounting for indels in…
Sven Schneider, Nico Hochgeschwender, Herman Bruyninckx
This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific computational building blocks that prevent code duplication and enable robots to adapt their software themselves. The…
Shuvendu K. Lahiri, Chao Wang, Yanju Chen, Chenglong Wang + 3 more
'Osbert Bastani' 'Isil Dillig' 'Yu Feng'] In this paper, we present a new program synthesis algorithm based on reinforcement learning. Given an initial policy (i.e. statistical model) trained off-line, our method uses this policy to guide its search and gradually improves it by leveraging feedback obtained from a…
Zhen Shang, Jin-Kao Hao, Fei Ma, Daniele D’Agostino
Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, scheduling interrelated activities in an appropriate sequence is an important issue for project managers. This study…