Design and Implementation of the UniProt Website

Jain, Eric; Phan, Isabelle; Duvaud, Séverine; Gasteiger, Elisabeth; Redaschi, Nicole; Martı́n, Marı́a Jesús; McGarvey, Peter B.; Bairoch, Amos Marc

doi:10.1038/npre.2008.2611.1

Cited by 3 publications

(2 citation statements)

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“…This database is a subset of the data used in [9] and includes 2544 proteins associated to the Em bryophyta taxonomy of the Uniprot database [13] with an notation in the GO project [1]. The dataset does not contain any protein sequences with a sequence identity higher than 2 30%.…”

Section: Molecular Function Datamentioning

confidence: 99%

A comparison of class-balance strategies for SVM in the problem of protein function prediction

Mercado-Diaz

Navarro-Garcia

Jaramillo-Garzón

2015

2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA)

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This paper presents a comparison of three strategies for managing the imbalance problem: undersampling, SMOTE and Weighted SVM. Undersampling is a strategy where the samples of the majority class are discarded; SMOTE (Syn thetic Minority Over-sampling Technique) is a method in which synthetic samples of the minority class are added to the dataset; Weighted SVM keeps the number of samples of each class but assigns weights in the training of the SVM, so it can improve its performance for the minority class. Results show that Weighted SVM and SMOTE achieved comparable results, although Weighted SVM requires less computational effort. Undersampling, on the other hand, achieved lower performance results presumably due to the loss of information produced when discarding data.

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Section: Molecular Function Datamentioning

confidence: 99%

A comparison of class-balance strategies for SVM in the problem of protein function prediction

Mercado-Diaz

Navarro-Garcia

Jaramillo-Garzón

2015

2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA)

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“…These technologies formalize how computers exchange messages, such as assignments, input data, computation results, and the output of database searches. SOAP and BioMoby are extensively used in life sciences [ 12 , 13 ], but the complexity and initial version incompatibilities of libraries that implement the SOAP specification have made REST an increasingly popular alternative [ 14 ]. While SOAP and BioMoby wrap the data in XML envelopes, REST can send around any data type.…”

Section: Introductionmentioning

confidence: 99%

XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

et al. 2009

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Background: Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in order to be effective. HTTP-based Web service technologies, like the Simple Object Access Protocol (SOAP) and REpresentational State Transfer (REST) services, are today the most common technologies for this in bioinformatics. However, these methods have severe drawbacks, including lack of discoverability, and the inability for services to send status notifications. Several complementary workarounds have been proposed, but the results are ad-hoc solutions of varying quality that can be difficult to use.

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Transcriptome Changes during the Life Cycle of the Red Sponge, Mycale phyllophila (Porifera, Demospongiae, Poecilosclerida)

Qiu

Ding

et al. 2015

Genes

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Sponges are an ancient metazoan group with broad ecological, evolutionary, and biotechnological importance. As in other marine invertebrates with a biphasic life cycle, the developing sponge undergoes a significant morphological, physiological, and ecological transformation during settlement and metamorphosis. In this study, we compare new transcriptome datasets for three life cycle stages of the red sponge (Mycale phyllophila) to test whether gene expression (as in the model poriferan, Amphimedon queenslandica) also varies more after settlement and metamorphosis. In contrast to A. queenslandica, we find that the transcriptome of M. phyllophila changes more during the earlier pre-competent larva/post-larva transition that spans these defining events. We also find that this transition is marked by a greater frequency of significantly up-regulated Gene Ontology terms including those for morphogenesis, differentiation, and development and that the transcriptomes of its pre-competent larvae and adult are distinct. The life cycle transcriptome variation between M. phyllophila and A. queenslandica may be due to their long separate evolutionary histories and corresponding differences in developmental rates and timing. This study now calls for new transcriptome datasets of M. phyllophila and other sponges, which will allow for tests of the generality of our life cycle expression differences and for the greater exploitation of poriferans in both basic and applied research.

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Design and Implementation of the UniProt Website

Cited by 3 publications

References 0 publications

A comparison of class-balance strategies for SVM in the problem of protein function prediction

A comparison of class-balance strategies for SVM in the problem of protein function prediction

XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

Transcriptome Changes during the Life Cycle of the Red Sponge, Mycale phyllophila (Porifera, Demospongiae, Poecilosclerida)

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