Precise annotation

Clinical genomic testing is dependent on the robust identification and reporting of variant-level information in relation to disease. With the shift to high-throughput sequencing, a major challenge for clinical diagnostics is the cross-identification of variants called on their genomic position to resources that rely on transcript- or protein-based descriptions.

14p vioraclene 31-03-2024 3 2   Download

As clinical trials evolve in complexity, clinical trial data models that can capture relevant trial data in meaningful, structured annotations and computable forms are needed to support accrual.

10p vighostrider 25-05-2023 7 2   Download

Weed identification helps ensure crop yield and realize precision agriculture. Although the deep learning-based methods have achieved high performance, their needed large-scale annotated data is difficult to obtain, and the massive parameters lead to difficulties in model deployment in embedded applications. To develop efficient crop weeds classification system, we propose a dissimilarity-based method to select few but representative samples and consider data diversity.

12p lyhuyenthu 31-01-2023 9 3   Download

To discover driver fusions beyond canonical exon-to-exon chimeric transcripts, we develop CICERO, a local assembly-based algorithm that integrates RNA-seq read support with extensive annotation for candidate ranking. CICERO outperforms commonly used methods, achieving a 95% detection rate for 184 independently validated driver fusions including internal tandem duplications and other noncanonical events in 170 pediatric cancer transcriptomes.

18p viarchimedes 26-01-2022 10 0   Download

High throughput sequencing technologies have been an increasingly critical aspect of precision medicine owing to a better identification of disease targets, which contributes to improved health care cost and clinical outcomes. In particular, disease-oriented targeted enrichment sequencing is becoming a widely-accepted application for diagnostic purposes, which can interrogate known diagnostic variants as well as identify novel biomarkers from panels of entire human coding exome or disease-associated genes.

11p vibeauty 23-10-2021 14 1   Download

The advent and ongoing development of next generation sequencing technologies (NGS) has led to a rapid increase in the rate of human genome re-sequencing data, paving the way for personalized genomics and precision medicine. The body of genome resequencing data is progressively increasing underlining the need for accurate and time-effective bioinformatics systems for genotyping - a crucial prerequisite for identification of candidate causal mutations in diagnostic screens.

9p vibeauty 23-10-2021 9 0   Download

In the present study, we used long-PCR amplification coupled with Next-Generation Sequencing (NGS) to obtain complete mitochondrial (mt) genomes of individual ticks and unprecedently performed precise annotation of these mt genomes.

11p vijeeni2711 24-07-2021 13 0   Download

Next-generation sequencing (NGS) is an efficient tool used for identifying pathogenic variants that cause Mendelian disorders. However, the lack of bioinformatics training of researchers makes the interpretation of identified variants a challenge in terms of precision and efficiency.

9p vilichoo2711 23-06-2021 16 1   Download

Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular.

11p vikentucky2711 26-11-2020 11 0   Download

Accurate computational identification of eukaryotic gene organization is a long-standing problem. Despite the fundamental importance of precise annotation of genes encoded in newly sequenced genomes, the accuracy of predicted gene structures has not been critically evaluated, mostly due to the scarcity of proper assessment methods.

13p vikentucky2711 26-11-2020 10 0   Download

Next Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data.

10p vijisoo2711 27-10-2020 8 0   Download

The performance of computer aided ECG analysis depends on the precise and accurate delineation of QRS-complexes. This paper presents an application of K-Nearest Neighbor (KNN) algorithm as a classifier for detection of QRS-complex in ECG. The proposed algorithm is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhythmia database. In this work, a digital band-pass filter is used to reduce false detection caused by interference present in ECG signal and further gradient of the signal is used as a feature for QRS-detection.

14p kethamoi1 17-11-2019 21 0   Download

Reversal of carbapenem-resistance in Shewanella algae by CRISPR/Cas9 genome editing Antibiotic resistance in pathogens is a growing threat to human health. Of particular concern is resistance to carbapenem, which is an antimicrobial agent listed as critically important by the World Health Organization. With the global spread of carbapenem-resistant organisms, there is an urgent need for new treatment options. Shewanella algae is an emerging pathogen found in marine environments throughout the world that has increasing resistance to carbapenem.

9p caygaocaolon1 13-11-2019 17 0   Download

We consider the problem of NER in Arabic Wikipedia, a semisupervised domain adaptation setting for which we have no labeled training data in the target domain. To facilitate evaluation, we obtain annotations for articles in four topical groups, allowing annotators to identify domain-specific entity types in addition to standard categories. Standard supervised learning on newswire text leads to poor target-domain recall.

12p bunthai_1 06-05-2013 53 2   Download

This paper addresses the problem of extracting the most important facts from a news article. Our approach uses syntactic, semantic, and general statistical features to identify the most important sentences in a document. The importance of the individual features is estimated using generalized iterative scaling methods trained on an annotated newswire corpus.

9p bunthai_1 06-05-2013 29 1   Download

This paper presents PEAS, the first comparative evaluation framework for parsers of French whose annotation formalism allows the annotation of both constituents and functional relations. A test corpus containing an assortment of different text types has been built and part of it has been manually annotated. Precision/Recall and crossing brackets metrics will be adapted to our formalism and applied to the parses produced by one parser from academia and another one from industry in order to validate the framework. ...

4p bunthai_1 06-05-2013 57 2   Download

We propose a new method for detecting errors in "gold-standard" part-ofspeech annotation. The approach locates errors with high precision based on n-grams occurring in the corpus with multiple taggings. Two further techniques, closed-class analysis and finitestate tagging guide patterns, are discussed. The success of the three approaches is illustrated for the Wall Street Journal corpus as part of the Penn Treebank.

8p bunthai_1 06-05-2013 39 2   Download

In this paper we present a quantitative and qualitative analysis of annotation in the Hinoki treebank of Japanese, and investigate a method of speeding annotation by using part-of-speech tags. The Hinoki treebank is a Redwoods-style treebank of Japanese dictionary definition sentences. 5,000 sentences are annotated by three different annotators and the agreement evaluated. An average agreement of 65.4% was found using strict agreement, and 83.5% using labeled precision. Exploiting POS tags allowed the annotators to choose the best parse with 19.5% fewer decisions. ...

8p bunbo_1 17-04-2013 37 4   Download

To facilitate the use of syntactic information in the study of child language acquisition, a coding scheme for Grammatical Relations (GRs) in transcripts of parent-child dialogs has been proposed by Sagae, MacWhinney and Lavie (2004). We discuss the use of current NLP techniques to produce the GRs in this annotation scheme. By using a statistical parser (Charniak, 2000) and memorybased learning tools for classification (Daelemans et al., 2004), we obtain high precision and recall of several GRs. ...

8p bunbo_1 17-04-2013 42 5   Download

We investigate automatic classification of speculative language (‘hedging’), in biomedical text using weakly supervised machine learning. Our contributions include a precise description of the task with annotation guidelines, analysis and discussion, a probabilistic weakly supervised learning model, and experimental evaluation of the methods presented. We show that hedge classification is feasible using weakly supervised ML, and point toward avenues for future research.

8p hongvang_1 16-04-2013 43 2   Download