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Graph clustering
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Ebook "Computational biology: Issues and applications in oncology" provides a comprehensive report on recent techniques and results in computational oncology essential to the knowledge of scientists, engineers, as well as postgraduate students working on the areas of computational biology, bioinformatics, and medical informatics. With chapters timely prepared and written by experts in the field, this in-depth and up-to-date volume covers advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, image and pattern analysis applied to cancer research.
309p
cotieubac1004
15-03-2024
4
0
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Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out intercellular communications.
15p
vicwell
29-02-2024
5
2
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Ebook "Link mining: Models, algorithms, and applications" has become an emerging field of data mining, which has a high impact in various important applications such as text mining, social network analysis, collaborative filtering, and bioinformatics. This will be the first book on the market focusing on the theory and techniques as well as the related applications for link mining.
580p
tachieuhoa
28-01-2024
9
2
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This book evolved over the past ten years from a set of lecture notes developed while teaching the undergraduate Algorithms course at Berkeley and U.C. San Diego. Our way of teaching this course evolved tremendously over these years in a number of directions, partly to address our students’ background (undeveloped formal skills outside of programming), and partly to reflect the maturing of the field in general, as we have come to see it.
318p
haojiubujain08
01-11-2023
4
0
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In this paper, we present an algorithm to find overlapping communities in very large social networks. The algorithm is based on the label propagation technique, and we find the overlapping communities in the network by improving the clustering coefficient.
16p
vimulcahy
18-09-2023
7
4
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Text stream clustering is considered as a primitive task in natural language processing (NLP) which contains unique challenges related to the sparsity/noise, infinite length and cluster evolution of the input documents.
10p
viannee
02-08-2023
7
3
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Data clustering tools can uncover new knowledge to be used in cancer diagnosis and treatment. In this study, we proposed a novel method to cluster records of a relation. First, we designed an algorithm that calculates the similarity between record pairs of the relation, and then this similarity measure was used to generate a network corresponding to the relation.
17p
viannee
02-08-2023
8
3
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Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions (https://github.com/theislab/paga).
9p
vigalileogalilei
27-02-2022
14
1
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We describe a methodology for partitioning scRNA-seq datasets into metacells: disjoint and homogenous groups of profiles that could have been resampled from the same cell. Unlike clustering analysis, our algorithm specializes at obtaining granular as opposed to maximal groups.
19p
vielonmusk
30-01-2022
12
0
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SCANPY is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks.
5p
vialfrednobel
29-01-2022
6
0
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Chromosome conformation capture methods are being increasingly used to study three-dimensional genome architecture in multiple cell types and species. An important challenge is to examine changes in three-dimensional architecture across cell types and species. We present Arboretum-Hi-C, a multi-task spectral clustering method, to identify common and context-specific aspects of genome architecture.
18p
viaristotle
29-01-2022
7
0
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The evaluation shows how the achieved solutions provide a great performance improvement (between 70% and 90% of filtering time reduction) in a centralized configuration and how they may be used to achieve efficient subgraph searching over very large databases in cluster configurations.
17p
guernsey
28-12-2021
9
0
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To determine the relationship between clusters of back pain and joint pain and prescription opioid dispensing. Of 11,221 middle-aged participants from the Australian Longitudinal Study of Women’s Health, clusters of back pain and joint pain from 2001 to 2013 were identifed using group-based trajectory modelling. Prescription opioid dispensing from 2003 to 2015 was identifed by linking the cohort to Pharmaceutical Beneft Scheme dispensing data. Multinomial logistic regression was used to examine the association between back pain and joint pain clusters and dispensing of prescription opioids.
9p
vimackenziebezos
30-11-2021
14
1
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Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species.
12p
vibeauty
23-10-2021
6
1
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The repetitive content of the genome, once considered to be “junk DNA”, is in fact an essential component of genomic architecture and evolution. In this study, we used the genomes of three varieties of Cannabis sativa, three varieties of Humulus lupulus and one genotype of Morus notabilis to explore their repetitive content using a graph-based clustering method, designed to explore and compare repeat content in genomes that have not been fully assembled.
9p
vibeauty
23-10-2021
10
0
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The detection of protein complexes is of great significance for researching mechanisms underlying complex diseases and developing new drugs. Thus, various computational algorithms have been proposed for protein complex detection.
28p
visilicon2711
20-08-2021
8
1
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In this paper, we propose a semisupervised graph based clustering algorithm that tries to use seeds and constraints in the clustering process, called MCSSGC. Moreover, we also introduce a simple but efficient active learning method to collect the constraints that can boost the performance of MCSSGC, named KMMFFQS. These obtained results show that the proposed algorithm can significantly improve the clustering process compared to some recent algorithms.
19p
nguaconbaynhay11
07-04-2021
14
1
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In the present study we have used a graph-based method by utilizing Orthovenn 2 tool for orthologous analysis to compare and annotate the orthologous cluster between the genome of Anguina tritici, Ditylenchus destructor and Meloidogyne incognita.
8p
chauchaungayxua10
18-03-2021
10
2
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Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts).
15p
viwyoming2711
16-12-2020
11
0
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It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of “driver” mutations that are primarily responsible for tumorigenesis.
15p
vikentucky2711
26-11-2020
13
1
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