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Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for…

Neural and Evolutionary Computing · Computer Science 2017-10-31 Chen Chen , Changtong Luo , Zonglin Jiang

Software systems continuously evolve due to new functionalities, requirements, or maintenance activities. In the context of software evolution, software refactoring has gained a strategic relevance. The space of possible software…

Software Engineering · Computer Science 2024-01-31 Vittorio Cortellessa , Daniele Di Pompeo , Michele Tucci

The study of biological processes can greatly benefit from tools that automatically predict gene functions or directly cluster genes based on shared functionality. Existing data mining methods predict protein functionality by exploiting…

Machine Learning · Computer Science 2020-11-20 Kaiyu Shen , Razvan Bunescu , Sarah E. Wyatt

The worldwide surge of multiresistant microbial strains has propelled the search for alternative treatment options. The study of Protein-Protein Interactions (PPIs) has been a cornerstone in the clarification of complex physiological and…

Sequence alignment is common nowadays as it is used in many fields to determine how closely two sequences are related and at times to see how little they differ. In computational biology / Bioinformatics, there are many algorithms developed…

Information Theory · Computer Science 2023-05-02 Bharath Reddy , Richard Fields

High throughput technologies have become the practice of choice for comparative studies in biomedical applications. Limited number of sample points due to sequencing cost or access to organisms of interest necessitates the development of…

Methodology · Statistics 2018-07-17 Ariana Broumand , Siamak Zamani Dadaneh

The reliability of a high-throughput biological experiment relies highly on the settings of the operational factors in its experimental and data-analytic procedures. Understanding how operational factors influence the reproducibility of the…

Methodology · Statistics 2018-07-04 Feipeng Zhang , Frank Shen , Tao Yang , Qunhua Li

In this paper, we formulate the hyperparameter tuning problem in machine learning as a bilevel program. The bilevel program is solved using a micro genetic algorithm that is enhanced with a linear program. While the genetic algorithm…

Machine Learning · Computer Science 2024-07-02 Ankur Sinha , Paritosh Pankaj

High throughput sequencing (HTS)-based technology enables identifying and quantifying non-culturable microbial organisms in all environments. Microbial sequences have enhanced our understanding of the human microbiome, the soil and plant…

Applications · Statistics 2021-03-09 Pratheepa Jeganathan , Susan P. Holmes

This paper describes a new QR factorization algorithm which is especially designed for massively parallel platforms combining parallel distributed multi-core nodes. These platforms make the present and the foreseeable future of…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-08-27 Jack Dongarra , Mathieu Faverge , Thomas Herault , Julien Langou , and Yves Robert

Adaptive indexing is a concept that considers index creation in databases as a by-product of query processing; as opposed to traditional full index creation where the indexing effort is performed up front before answering any queries.…

Databases · Computer Science 2014-04-09 Victor Alvarez , Felix Martin Schuhknecht , Jens Dittrich , Stefan Richter

Mixed-integer optimisation problems can be computationally challenging. Here, we introduce and analyse two efficient algorithms with a specific sequential design that are aimed at dealing with sampled problems within this class. At each…

Optimization and Control · Mathematics 2023-03-07 Mohammadreza Chamanbaz , Roland Bouffanais

Microbial clades modeling is a challenging problem in biology based on microarray genome sequences, especially in new species gene isolates discovery and category. Marker family genome sequences play important roles in describing specific…

Quantitative Methods · Quantitative Biology 2019-04-22 Jingwei Liu

We propose RoBiRank, a ranking algorithm that is motivated by observing a close connection between evaluation metrics for learning to rank and loss functions for robust classification. The algorithm shows a very competitive performance on…

Machine Learning · Statistics 2014-08-22 Hyokun Yun , Parameswaran Raman , S. V. N. Vishwanathan

Identifying operons is a fundamental step in understanding prokaryotic gene regulation, as classifying genes into operons supports the reconstruction of regulatory networks, functional annotation of unannotated genes, and drug candidate…

Genomics · Quantitative Biology 2026-05-13 Akarsh Gupta , Kenneth Rodrigues , Sagnik Chatterjee

Huge amount of data in the form of strings are being handled in bio-computing applications and searching algorithms are quite frequently used in them. Many methods utilizing on both software and hardware are being proposed to accelerate…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-31 D. Herath , C. Lakmali , R. G. Ragel

Genome sequencing is essential to decode genetic information, identify organisms, understand diseases and advance personalized medicine. A critical step in any genome sequencing technique is genome assembly. However, de novo genome…

Computational methods for discovering patterns of local correlations in sequences are important in computational biology. Here we show how to determine the optimal partitioning of aligned sequences into non-overlapping segments such that…

Computational Engineering, Finance, and Science · Computer Science 2012-06-26 Joseph Bockhorst , Nebojsa Jojic

The search for similar genetic sequences is one of the main bioinformatics tasks. The genetic sequences data banks are growing exponentially and the searching techniques that use linear time are not capable to do the search in the required…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-13 Felipe Albrecht

In this paper we describe SYNERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world it is planning for, SYNERGY uses artificial selection,…

Artificial Intelligence · Computer Science 2007-05-23 Ion Muslea
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