Featured videos
View featured videos from across the BMC-series journals
Page 4 of 33
Scientific names in biology act as universal links. They allow us to cross-reference information about organisms globally. However variations in spelling of scientific names greatly diminish their ability to i...
Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an ard...
We conclude that an SSC can be a viable alternative for or a supplement to a GSC when training chunkers in a biomedical domain. A combined system only shows improvement if the SSC is used to supplement a GSC. Whe...
The integration of the rapidly expanding corpus of information about the genome, transcriptome, and proteome, engendered by powerful technological advances, such as microarrays, and the availability of genomic se...
With more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing complexity of requirements of informed consent forms. The aim of this study is ...
Automatic recognition of biomedical names is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. In recent years, various solutions have been implemented...
There are millions of public posts to medical message boards by users seeking support and information on a wide range of medical conditions. It has been shown that these posts can be used to gain a greater und...
Neural network based embedding models are receiving significant attention in the field of natural language processing due to their capability to effectively capture...
Despite the many progresses with alignment algorithms, aligning divergent protein sequences with less than 20–35% pairwise identity (so called "twilight zone") remains a difficult problem. Many alignment algor...
Alkaline earth metal ions are important protein binding ligands in human body, and it is of great significance to predict their binding residues.
Natural language processing (NLP) and text mining technologies for...
Twitter is a popular social networking site where short messages or “tweets” of users have been used extensively for research purposes. However, not much research has been done in mining the medical profession...
The accelerating pace of biomedical publication has made it impractical to manually, systematically identify papers containing specific information and extract this information. This is especially challenging ...
Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for query...
The manual diagnosis of neurodegenerative disorders such as Alzheimer’s disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic crit...
The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction...
The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behavio...
The expansion of research across various disciplines has led to a substantial increase in published papers and journals, highlighting the necessity for reliable text mining platforms for database construction ...
A word embedding strategy commonly used in natural language processing was utilized in order to generate gene...
Model card reports aim to provide informative and transparent description of machine learning models to stakeholders. This report document is of interest to the National Institutes of Health’s Bridge2AI initia...
We aim to solve the problem of determining word senses for ambiguous biomedical terms with minimal human effort.
Most biomedical information extraction focuses on binary relations within single sentences. However, extracting n-ary relations that span multiple sentences is in huge demand. At present, in the cross-sentence...
All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being des...
Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at a...
The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational method...
In this study, we developed MHCSeqNet, an open-source deep learning model, which not only outperforms state-of-the-art predictors on both MHC binding affinity and MHC ligand peptidome datasets but also exhibits p...
Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. T...
The Internet is a major source of health information but most seekers are not familiar with medical vocabularies. Hence, their searches fail due to bad query formulation. Several methods have been proposed to ...
Electronic medical records (EMR) contain detailed information about patient health. Developing an effective representation model is of great significance for the downstream applications of EMR. However, proces...
Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools ...
It is understood that cancer is a clonal disease initiated by a single cell, and that metastasis, which is the spread of cancer from the primary site, is also initiated by a single cell. The seemingly natural ...
In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural language sentences. We approach this problem by building ... Machine, ...
Lately, there has been a great interest in the application of information extraction methods to the biomedical domain, in particular, to the extraction of relationships of genes, proteins, and RNA from scienti...
Small molecules are of increasing interest for bioinformatics in areas such as metabolomics and drug discovery. The recent release of large open access chemistry databases generates a demand for flexible tools...
The detection and interpretation of CNVs are of clinical importance in genetic testing. Several databases and web services are already being used by clinical geneticists to interpret the medical relevance of i...
The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world of bioinformatics services. Without adequate management and development suppo...
Information Extraction (IE) is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge document collections. As events are...
In this work we describe an approach that facilitates the automatic recognition of eight relationships defined between medical problems, treatments and tests. Unlike the traditional bag-of-words representation, i...
Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in dynamic contrast-enhanced (DCE) magnetic resonance...
Biomedical named entity recognition (BioNER) is a basic and important medical information extraction task to extract medical entities with special meaning from medical texts. In recent years, deep learning has...
A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. ...
Biological contextual information helps understand various phenomena occurring in the biological systems consisting of complex molecular relations. The construction of context-specific relational resources vas...
With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation ...
Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human r...
The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order to support clinical research, evidence-ba...
Elucidation of interactive relation between chemicals and genes is of key relevance not only for discovering new drug leads in drug development but also for repositioning existing drugs to novel therapeutic ta...
As Twitter has become an active data source for health surveillance research, it is important that efficient and effective methods are developed to identify tweets related to personal health experience. Conven...
Making accurate patient care decision, as early as possible, is a constant challenge, especially for physicians in the emergency department. The increasing volumes of electronic medical records (EMRs) open new...
Mathematical and computational modelling of biochemical systems has seen a lot of effort devoted to the definition and implementation of high-performance mechanistic simulation frameworks. Within these framewo...
View featured videos from across the BMC-series journals
2022 Citation Impact
3.0 - 2-year Impact Factor
4.3 - 5-year Impact Factor
0.938 - SNIP (Source Normalized Impact per Paper)
1.100 - SJR (SCImago Journal Rank)
2023 Speed
19 days submission to first editorial decision for all manuscripts (Median)
146 days submission to accept (Median)
2023 Usage
5,987,678 downloads
4,858 Altmetric mentions