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Related papers: Haplotype-resolved de novo assembly with phased as…

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A hypercomplex representation of DNA is proposed to facilitate comparison of DNA sequences with fuzzy composition. Using hypercomplex number representation, conventional sequence analysis method, such as, dot matrix analysis, dynamic…

Quantitative Methods · Quantitative Biology 2023-08-03 Jian-Jun Shu , Yajing Li

De novo prediction of protein structures, the prediction of structures from amino-acid sequences which are not similar to those of hitherto resolved structures, has been one of the major challenges in molecular biophysics. In this paper, we…

Biomolecules · Quantitative Biology 2008-02-22 Takeshi N. Sasaki , Hikmet Cetin , Masaki Sasai

Segmental duplications (SDs), or low-copy repeats (LCR), are segments of DNA greater than 1 Kbp with high sequence identity that are copied to other regions of the genome. SDs are among the most important sources of evolution, a common…

Data Structures and Algorithms · Computer Science 2018-09-25 Ibrahim Numanagić , Alim S. Gökkaya , Lillian Zhang , Bonnie Berger , Can Alkan , Faraz Hach

Standard resampling ratios (e.g., $\alpha \approx 0.632$) are widely used as default baselines in ensemble learning for three decades. However, how these ratios interact with a base learner's intrinsic functional complexity in finite…

Machine Learning · Computer Science 2026-04-14 Ye Su , Mingrui Ye , Yining Wang , Jipeng Guo , Yong Liu

Affordable, high-quality whole-genome assemblies have made it possible to construct rich pangenomes that capture haplotype diversity across many species. As these datasets grow, they motivate the development of specialized techniques…

Genomics · Quantitative Biology 2025-12-19 Gorkem Kadir Solun , Ugur Dogrusoz

We propose an assembly algorithm {\sc Barnacle} for sequences generated by the clone-based approach. We illustrate our approach by assembling the human genome. Our novel method abandons the original physical-mapping-first framework. As we…

Data Structures and Algorithms · Computer Science 2007-05-23 Vicky Choi , Martin Farach-Colton

The perennial problem of "how many clusters?" remains an issue of substantial interest in data mining and machine learning communities, and becomes particularly salient in large data sets such as populational genomic data where the number…

Machine Learning · Statistics 2009-08-20 Kyung-Ah Sohn , Eric P. Xing

We consider a novel approach of measuring the homology of DNA sequences based of the variety of optimal alignments in the longest common subsequence sense. The proposed approach is compared with BLAST in measuring the homology of four…

Applications · Statistics 2012-10-16 Erik Hirmo , Jüri Lember , Heinrich Matzinger

Low-coverage short-read resequencing experiments have the potential to expand our understanding of Y chromosome haplogroups. However, the uncertainty associated with these experiments mean that haplogroups must be assigned probabilistically…

Populations and Evolution · Quantitative Biology 2014-07-31 Luke Jostins , Yali Xu , Shane McCarthy , Qasim Ayub , Richard Durbin , Jeff Barrett , Chris Tyler-Smith

Motivation: Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls…

Genomics · Quantitative Biology 2018-07-27 Heng Li

The de Bruijn graph plays an important role in bioinformatics, especially in the context of de novo assembly. However, the representation of the de Bruijn graph in memory is a computational bottleneck for many assemblers. Recent papers…

Quantitative Methods · Quantitative Biology 2014-10-07 Rayan Chikhi , Antoine Limasset , Shaun Jackman , Jared Simpson , Paul Medvedev

Graph clustering, an important unsupervised problem, has been shown to be more resistant to advances in Graph Neural Networks (GNNs). In addition, almost all clustering methods focus on homophilic graphs and ignore heterophily. This…

Machine Learning · Computer Science 2026-03-11 Xuanting Xie , Erlin Pan , Zhao Kang , Wenyu Chen , Bingheng Li

We study homomorphism polynomials, which are polynomials that enumerate all homomorphisms from a pattern graph $H$ to $n$-vertex graphs. These polynomials have received a lot of attention recently for their crucial role in several new…

Computational Complexity · Computer Science 2020-11-17 Balagopal Komarath , Anurag Pandey , C. S. Rahul

Homomorphism is a key mapping technique between graphs that preserves their structure. Given a graph and a pattern, the subgraph homomorphism problem involves finding a mapping from the pattern to the graph, ensuring that adjacent vertices…

Artificial Intelligence · Computer Science 2025-12-18 Shuyang Guo , Wenjin Xie , Ping Lu , Ting Deng , Richong Zhang , Jianxin Li , Xiangping Huang , Zhongyi Liu

Reducing the cost of sequencing genomes provided by next-generation sequencing technologies has greatly increased the number of genomic projects. As a result, there is a growing need for better assembly and assembly validation methods. One…

Genomics · Quantitative Biology 2022-10-17 Przemysław Stawczyk , Robert Nowak

Modern high-throughput sequencing assays efficiently capture not only gene expression and different levels of gene regulation but also a multitude of genome variants. Focused analysis of alternative alleles of variable sites at homologous…

Data heterogeneity is one of the major challenges in federated learning (FL), which results in substantial client variance and slow convergence. In this study, we propose a novel solution: decomposing a convolutional filter in FL into a…

Machine Learning · Computer Science 2025-03-12 Wei Chen , Qiang Qiu

Given a set of data, biclustering aims at finding simultaneous partitions in biclusters of its samples and of the features which are used for representing the samples. Consistent biclusterings allow to obtain correct classifications of the…

Machine Learning · Computer Science 2010-03-18 Antonio Mucherino , Sonia Cafieri

In this paper we present a model containing modifications to the Signal-passing Tile Assembly Model (STAM), a tile-based self-assembly model whose tiles are capable of activating and deactivating glues based on the binding of other glues.…

Emerging Technologies · Computer Science 2022-03-30 Andrew Alseth , Daniel Hader , Matthew J. Patitz

As mixing services are increasingly being exploited by malicious actors for illicit transactions, mixing address association has emerged as a critical research task. A range of approaches have been explored, with graph-based models standing…

Social and Information Networks · Computer Science 2025-11-18 Xiaofan Tu , Tiantian Duan , Shuyi Miao , Hanwen Zhang , Yi Sun