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Manual curation of biological databases, an expensive and labor-intensive process, is essential for high quality integrated data ... the implementation of a state-of-the-art Natural Language Processing system tha...
Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this...
Natural Language Processing (NLP) has been shown effective to...
The Enteropathogen Resource Integration Center (ERIC; http://www.ericbrc.org) has a goal of providing bioinformatics support for the scientific communi...
Many biomedical natural language processing systems demonstrated large differences between their previously...
The abundance of biomedical text data coupled with advances in natural language processing (NLP) is resulting in novel biomedical ... are reliant on the availability of domain-specific language models (LMs) that ...
We present an extension of the TM tool, which utilizes natural language processing (NLP) for analyzing the context of ... the global low-resolution docking scan was post-processed, separately, by constraints from...
Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local r...
We report the development and evaluation of Microbial Phenomics Information Extractor (MicroPIE, version 0.1.0). MicroPIE is a natural language processing application that uses a robust supervised classification....
Natural language processing (NLP) applications are increasingly important in...
Interest is growing in the application of syntactic parsers to natural language processing problems in biology, but assessing their performance...
Applications of Natural Language Processing (NLP) technology to biomedical texts have...subdomain variation within the biomedical domain, i.e., the extent to which different subject areas of biomedicine are chara...
Metabolic flux analysis has become an established method in systems biology and functional genomics. The most common approach for determining intracellular metabolic fluxes is to utilize mass spectrometry in c...
Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information ...
Gas chromatography–mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data ti...
Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis...
It has been suggested previously that genome and proteome sequences show characteristics typical of natural-language texts such as "signature-style" word ... , and that the algorithms originally developed for natural
We introduced a novel way to represent protein sequences as continuous vectors (embeddings) by using the language model ELMo taken from natural language processing. By modeling protein sequences, ELMo effectively...
The recognition of pharmacological substances, compounds and proteins is essential for biomedical relation extraction, knowledge graph construction, drug discovery, as well as medical question answering. Although...
Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i...
Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a ...
Biomedical question answering (QA) is a sub-task of natural language processing in a specific domain, which aims to ... the neural network and large scale pre-trained language model have largely improved its perf...
Due to the nature of scientific methodology, research articles are rich in speculative and tentative statements, also known as hedges. We explore a linguistically motivated approach to the problem of recognizi...
This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for bi...
Calcium (Ca2+) propagates within tissues serving as an important information carrier. In particular, cilia beat frequency in oviduct cells is partially regulated by Ca2+ changes. Thus, measuring the calcium de...
We present a literature-driven workflow involving document delivery and natural language processing steps generating tagged sentences containing lipid, protein...bibliosphere. We illustrate the extent of the desc...
Medical information has rapidly increased on the internet and has become one of the main targets of search engine use. However, medical information on the internet is subject to the problems of quality and acc...
Techniques from computational linguistics can provide new insights into the annotation process. GO annotations show similar statistical behaviours to those seen in natural language with measured exponents that pr...
During library construction polymerase chain reaction is used to enrich the DNA before sequencing. Typically, this process generates duplicate read sequences. Removal of these artifacts is mandatory, as they c...
Coreference resolution is the task of finding strings in text that have the same referent as other strings. Failures of coreference resolution are a common cause of false negatives in information extraction fr...
Automated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and the subject of many open shared ... the art involves the use of neural netw...
One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metab...
The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in th...
The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors in...
Genomic functional information is valuable for biomedical research. However, such information frequently needs to be extracted from the scientific literature and structured in order to be exploited by automatic s...
In the era of information overload, natural language processing (NLP) techniques are increasingly needed to...
The advent of population-scale genome projects has revolutionized our biological understanding of parasitic protozoa. However, while hundreds to thousands of nuclear genomes of parasitic protozoa have been gen...
Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Que...
Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, resea...
Data generated from liquid chromatography coupled to high-resolution mass spectrometry (LC-MS)-based studies of a biological sample can contain large amounts of biologically significant information in the form...
SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization co...
Tokenization is an important component of language processing yet there is no widely accepted tokenization method for English texts, including biomedical texts. Other than rule based techniques, tokenization i...
The volume of biomedical literature and clinical data is growing at an exponential rate. Therefore, efficient access to data described in unstructured biomedical texts is a crucial task for the biomedical indu...
Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic...
Here, we build an integrative platform, the E ncyclopedia of H epatocellular C arcinoma genes O nline, dubbed EHCO http://ehco.iis.sinica.edu.tw..., to syste...
We extracted semantic relations with the SemRep natural language processing system from 122,421,765 sentences, which ... organized in a relational database. The QA process is implemented as a search in this...
Syntactic analysis, or parsing, is a key task in natural language processing and a required component for many text...
The evolving complexity of genome-scale experiments has increasingly centralized the role of a highly computable, accurate, and comprehensive resource spanning multiple biological scales and viewpoints. To provid...
In this research, we proposed a model based on representation and attention mechanism based deep learning methods, to automatic annotate E3-substrate interaction sentences in biomedical literature. Focusing on th...
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Speed
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163 days from submission to acceptance
36 days from acceptance to publication
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3.169 - 2-year Impact Factor
3.629 - 5-year Impact Factor
1.276 - Source Normalized Impact per Paper (SNIP)
1.567 - SCImago Journal Rank (SJR)
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