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The chaos game representation (CGR) is an interesting method to visualize one-dimensional sequences. In this paper, we show how to construct a chaos game representation. The applications mentioned here are biological, in which CGR was able…

History and Overview · Mathematics 2020-12-18 Eunice Y. S. Chan , Robert M. Corless

A 3D chaos game is shown to be a useful way for encoding DNA sequences. Since matching subsequences in DNA converge in space in 3D chaos game encoding, a DNA sequence's 3D chaos game representation can be used to compare DNA sequences…

Genomics · Quantitative Biology 2024-11-11 Stephanie Young , Jerome Gilles

DNA sequences are fundamental for encoding genetic information. The genetic information may not only be understood by symbolic sequences but also from the hidden signals inside the sequences. The symbolic sequences need to be transformed…

Computational Engineering, Finance, and Science · Computer Science 2017-12-20 Changchuan Yin

This paper establishes formal mathematical foundations linking Chaos Game Representations (CGR) of DNA sequences to their underlying $k$-mer frequencies. We prove that the Frequency CGR (FCGR) of order $k$ is mathematically equivalent to a…

Formal Languages and Automata Theory · Computer Science 2025-07-01 Haoze He , Lila Kari , Pablo Millan Arias

Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Chaos Game Representation (MS-RCGR), that transforms biological sequences into…

Machine Learning · Computer Science 2026-04-21 Sarwan Ali , Taslim Murad

Graphs as a type of data structure have recently attracted significant attention. Representation learning of geometric graphs has achieved great success in many fields including molecular, social, and financial networks. It is natural to…

Machine Learning · Computer Science 2021-07-08 Tian Xia , Wei-Shinn Ku

This study proposes CGRclust, a novel combination of unsupervised twin contrastive clustering of Chaos Game Representations (CGR) of DNA sequences, with convolutional neural networks (CNNs). To the best of our knowledge, CGRclust is the…

Genomics · Quantitative Biology 2024-11-14 Fatemeh Alipour , Kathleen A. Hill , Lila Kari

Researchers in the field of DNA-based chaotic cryptography have recently proposed a set of novel and efficient image encryption algorithms. In this paper, we present a comprehensive summary of those techniques, which are available in the…

Cryptography and Security · Computer Science 2015-05-08 Chiranjoy Chattopadhyay , Bikramjit Sarkar , Debaprasad Mukherjee

In nature the three-dimensional structure of a protein is encoded in the corresponding gene. In this paper we describe a new method for encoding the three-dimensional structure of a protein into a binary sequence. The feature of the method…

Combinatorics · Mathematics 2007-05-23 Naoto Morikawa

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains…

Artificial Intelligence · Computer Science 2014-11-17 L. Leherte , J. Glasgow , K. Baxter , E. Steeg , S. Fortier

We present a novel information-preserving Chaos Game Representation (CGR) method, also called Reverse-CGR (R-CGR), for biological sequence analysis that addresses the fundamental limitation of traditional CGR approaches - the loss of…

Machine Learning · Computer Science 2025-09-25 Sarwan Ali

Protein folding produces characteristic and functional three-dimensional structures from unfolded polypeptides or disordered coils. The emergence of extraordinary complexity in the protein folding process poses astonishing challenges to…

Biomolecules · Quantitative Biology 2013-08-14 Kelin Xia , Guo-Wei Wei

We present a three-dimensional graph convolutional network (3DGCN), which predicts molecular properties and biochemical activities, based on 3D molecular graph. In the 3DGCN, graph convolution is unified with learning operations on the…

Machine Learning · Computer Science 2019-08-08 Hyeoncheol Cho , Insung S. Choi

We demonstrate the presence of chaos in stochastic simulations that are widely used to study biodiversity in nature. The investigation deals with a set of three distinct species that evolve according to the standard rules of mobility,…

Biological Physics · Physics 2017-03-28 D. Bazeia , M. B. P. N. Pereira , A. V. Brito , B. F. de Oliveira , J. G. G. S. Ramos

Nowadays, studying introns is becoming a very promising field in the genomics. Even though they play a role in the dynamic regulation of gene and in the organism's evolution, introns have not attracted enough attention like exons did;…

Systems and Control · Computer Science 2013-06-24 Imen Messaoudi , Afef Elloumi Oueslati , Zied Lachiri

In this work, we applied the Chaos Game Representation (CGR) to the complete human genomic sequence T2T-CHM13v2.0, analyzing the entire chromosome assembly and each chromosome separately, including mitochondrial DNA. Multifractal spectra…

Other Quantitative Biology · Quantitative Biology 2024-12-24 Yulián A. Alvarez-Ballesteros , Mario A. Quiroz-Juarez , José L. Del-Rio-Correa , Adrian M. Escobar-Ruiz

Initial protein structural comparisons were sequence-based. Since amino acids that are distant in the sequence can be close in the 3-dimensional (3D) structure, 3D contact approaches can complement sequence approaches. Traditional 3D…

Molecular Networks · Quantitative Biology 2017-03-01 Fazle E. Faisal , Julie L. Chaney , Khalique Newaz , Jun Li , Scott J. Emrich , Patricia L. Clark , Tijana Milenkovic

The analysis of sequences (e.g., protein, DNA, and SMILES string) is essential for disease diagnosis, biomaterial engineering, genetic engineering, and drug discovery domains. Conventional analytical methods focus on transforming sequences…

Quantitative Methods · Quantitative Biology 2025-03-20 Taslim Murad , Sarwan Ali , Murray Patterson

Motivation: Thanks to the recent advances in structural biology, nowadays three-dimensional structures of various proteins are solved on a routine basis. A large portion of these contain structural repetitions or internal symmetries. To…

Quantitative Methods · Quantitative Biology 2018-10-30 Guillaume Pagès , Sergei Grudinin

Dimensionality reduction is ubiquitous in analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Sergei V. Krivov
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