<b>dbscan</b>: Fast Density-Based Clustering with <i>R</i>

Hahsler, Michael; Piekenbrock, Matthew; Doran, Derek

doi:10.18637/jss.v091.i01

Cited by 503 publications

(370 citation statements)

References 48 publications

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“…In our experiments, we found that accurate detection could be performed even clustering a small number of points. The recommended number for DBSCAN's MinPts parameter is one more than the number of dimensions [23]. In our case, the number of dimensions is two − the interrupts over context switches ratio and the time.…”

Section: A Real-time Anomaly Detectionmentioning

confidence: 92%

Anomaly Detection for Science DMZs Using System Performance Data

Gegan

Mao

Ghosal

et al. 2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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Science DMZs are specialized networks that enable large-scale distributed scientific research, providing efficient and guaranteed performance while transferring large amounts of data at high rates. The high-speed performance of a Science DMZ is made viable via data transfer nodes (DTNs), therefore they are a critical point of failure. DTNs are usually monitored with network intrusion detection systems (NIDS). However, NIDS do not consider system performance data, such as network I/O interrupts and context switches, which can also be useful in revealing anomalous system performance potentially arising due to external network based attacks or insider attacks. In this paper, we demonstrate how system performance metrics can be applied towards securing a DTN in a Science DMZ network. Specifically, we evaluate the effectiveness of system performance data in detecting TCP-SYN flood attacks on a DTN using DBSCAN (a density-based clustering algorithm) for anomaly detection. Our results demonstrate that system interrupts and context switches can be used to successfully detect TCP-SYN floods, suggesting that system performance data could be effective in detecting a variety of attacks not easily detected through network monitoring alone.

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Section: A Real-time Anomaly Detectionmentioning

confidence: 92%

Anomaly Detection for Science DMZs Using System Performance Data

Gegan

Mao

Ghosal

et al. 2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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“…First, dimension reduction was executed on a combined data table of TSS normalized OTUs and ARGs and MGEs using t-SNE algorithm (29) and the R package Rtsne (55), with 50,000 iterations and “perplexity” set to 5. Then, clusters in the two-dimensional data were identified using HDBSCAN algorithm (30) in the package dbscan (56). The minimum number of members in clusters (“minPts”) was set to 3.…”

Section: Methodsmentioning

confidence: 99%

Swine Growth Promotion with Antibiotics or Alternatives can Increase Antibiotic Resistance Gene Mobility Potential

Muurinen¹,

Richert

Wickware³

et al. 2020

Preprint

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16The use of antimicrobials in animal production has been shown to increase the abundance of 17 antibiotic resistance genes (ARGs) in microbiomes and it is recommended by international health 18 organizations that the use of antimicrobial growth promoters would be restricted. Consequently, 19 the use alternative growth promoters is increasing, however, their influence on the collection of 20ARGs (the resistome) in the animal microbiome is understudied. We investigated the impact of 21 different growth promoters on the pig fecal resistome and microbiome. The growth promoters 22were carbadox (antibiotic), copper sulfate and zinc oxide (metal) or mushroom powder (natural 23 product). Six pens of seven weanling piglets per treatment were used in a growth trial and after 24 33 days, fecal samples were taken from one median weight female and male pig per pen. 25Samples from the same pen were pooled, and DNA was isolated. The community composition 26 was investigated by 16S rRNA gene sequencing and relative ARG and mobile genetic element 27 (MGE) abundances were measured using qPCR array with 382 primers. Only modest shifts were 28 observed in community structure and resistome in response to growth promoters, but more ARGs 29were co-occurring with MGEs in growth promoter group samples than in the control group 30 samples. The taxonomic structure could not be linked to resistome structure in the growth 31 promoter groups. The ARG-MGE co-occurrence patterns suggest that replacing the use of 32 antibiotics with alternative growth promoters might be an insufficient antibiotic resistance 33 mitigation strategy and active selection against ARGs will require a more comprehensive 34 approach. 35

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“…PCA on sRNAgenerating loci was performed in R with "FactoMineR" v1.42 (Lê et al, 2008) and "factoextra" v1.0.5 1 packages. HDBSCAN clustering was performed (parameters: minPts = 20) with dbscan R package v1.1-4 (Hahsler et al, 2019). Homology analysis of G. margarita-(Gma)-sRNA-generating loci with fungal repetitive elements from RepBase 23.04 2 was performed with tblastx (Evalue ≤ 0.00005) (Camacho et al, 2009).…”

Section: Bioinformatics Pipelinementioning

confidence: 99%

Different Genetic Sources Contribute to the Small RNA Population in the Arbuscular Mycorrhizal Fungus Gigaspora margarita

et al. 2020

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RNA interference (RNAi) is a key regulatory pathway of gene expression in almost all eukaryotes. This mechanism relies on short non-coding RNA molecules (sRNAs) to recognize in a sequence-specific manner DNA or RNA targets leading to transcriptional or post-transcriptional gene silencing. To date, the fundamental role of sRNAs in the regulation of development, stress responses, defense against viruses and mobile elements, and cross-kingdom interactions has been extensively studied in a number of biological systems. However, the knowledge of the "RNAi world" in arbuscular mycorrhizal fungi (AMF) is still limited. AMF are obligate mutualistic endosymbionts of plants, able to provide several benefits to their partners, from improved mineral nutrition to stress tolerance. Here we described the RNAi-related genes of the AMF Gigaspora margarita and characterized, through sRNA sequencing, its complex small RNAome, considering the possible genetic sources and targets of the sRNAs. G. margarita indeed is a mosaic of different genomes since it hosts endobacteria, RNA viruses, and nonintegrated DNA fragments corresponding to mitovirus sequences. Our findings show that G. margarita is equipped with a complete set of RNAi-related genes characterized by the expansion of the Argonaute-like (AGO-like) gene family that seems a common trait of AMF. With regards to sRNAs, we detected populations of sRNA reads mapping to nuclear, mitochondrial, and viral genomes that share similar features (25-nt long and 5 -end uracil read enrichments), and that clearly differ from sRNAs of endobacterial origin. Furthermore, the annotation of nuclear loci producing sRNAs suggests the occurrence of different sRNA-generating processes. In silico analyses indicate that the most abundant G. margarita sRNAs, including those of viral origin, could target transcripts in the host plant, through a hypothetical cross-kingdom RNAi.

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dbscan: Fast Density-Based Clustering with R

Cited by 503 publications

References 48 publications

Anomaly Detection for Science DMZs Using System Performance Data

Anomaly Detection for Science DMZs Using System Performance Data

Swine Growth Promotion with Antibiotics or Alternatives can Increase Antibiotic Resistance Gene Mobility Potential

Different Genetic Sources Contribute to the Small RNA Population in the Arbuscular Mycorrhizal Fungus Gigaspora margarita

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