Biological information extraction and co-occurrence analysis

Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen

PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinct subtypes of PCOS, while bio-markers and expression patterns for NA PCOS and HA PCOS have not been disclosed. We performed microarray analysis on granusola cells from NA PCOS, HA PCOS and normal tissue from 12 individuals. Afterwards, microarray data were processed and specific genes for NA PCOS and HA PCOS were identified. Further functional analysis selected IL6R and CD274 as new NA PCOS functional markers, and meanwhile selected CASR as new HA PCOS functional marker. IL6R, CD274 and CASR were afterwards experimentally validated on mRNA and protein level. Subsequent causal relationship analysis based on Apriori Rules Algorithm and co-occurrence methods identified classification markers for NA PCOS and HA PCOS. According to classification markers, downloaded transcriptome datasets were merged with our microarray data. Based on merged data, causal knowledge graph was constructed for NA PCOS or HA PCOS and female infertility on NA PCOS and HA PCOS. Gene-drug interaction analysis was then performed and drugs for HA PCOS and NA PCOS were predicted. Our work was among the first to indicate the NA PCOS and HA PCOS functional and classification markers and using markers to construct knowledge graphs and afterwards predict drugs for NA PCOS and HA PCOS based on transcriptome data. Thus, our study possessed biological and clinical value on further understanding the inner mechanism on the difference between NA PCOS and HA PCOS.

A bibliometric analysis in venous thromboembolism nursing (1999-2022): Current status and future prospects

Research on venous thromboembolism (VTE) in nursing has garnered significant attention. This study aimed to examine the characteristics of VTE nursing publications, offering valuable insights into the current state of the field and forecasting future trends. A comprehensive screening of global publications up to 2022 was conducted using the Web of Science Core Collection database to investigate VTE nursing. The search incorporated keywords such as 'venous thromboembolism', 'deep vein thrombosis', and 'pulmonary embolism' to identify relevant studies. A bibliometric analysis of these publications was performed using various visualisation tools such as VOSviewer and R software. A total of 675 papers on VTE nursing were identified, with the earliest publication dating back to 1999. The research involved 971 institutions from 43 countries, with the United States leading by contributing to 261 articles. Harvard University emerged as the most productive institution, and Heit, with 17 publications, was the most cited author. The journal Thrombosis Research published the highest number of papers (11). The frontiers of VTE nursing research are anticipated to continue focusing on topics such as epidemiology, risk factors, and VTE prevention and management.

Depicting Developing Trend and Core Knowledge of Primary Open-Angle Glaucoma: A Bibliometric and Visualized Analysis

Objective

The prevalence of glaucoma is rising due to an increasing aging population. Because of its insidious and irreversible nature, glaucoma has gradually become the focus of attention. We assessed primary open angle glaucoma, the most common type of glaucoma, to study its present status, global trend, and state of clinical research.

Methods

Publications from 2000 to 2021 in Web of Science database were retrieved and analyzed by bibliometrics. VOSviewer and Citespace were used for analysis.

Results

A total of 6,401 publications were included in this review, and we found that the number of publications increased from 139 in 2000 to 563 in 2021. American researchers have published the most papers and had the highest h-index and the most citations, while the Journal of Glaucoma has published the most papers on this topic. Some key researchers, contributing institutions, their partnerships, and scientific masterpieces were identified. The publications we reviewed fall into seven categories: publications on intraocular pressure, normal tension glaucoma, risk factors, the trabecular meshwork, optical coherence tomography, surgery, and mutation. Clear study hotspots were described, which began with epidemiology and transitioned to pathogenesis and diagnosis and then to treatment.

Conclusion

Studies on primary open angle glaucoma extend well beyond ophthalmology to biochemistry molecular biology, general internal medicine, pharmacology, pharmacy, science technology, and other areas. Interest, research and publications on primary open angle glaucoma are on the rise.

The speed of information propagation in the scientific network distorts biomedical research

Delays in the propagation of scientific discoveries across scientific communities have been an oft-maligned feature of scientific research for introducing a bias towards knowledge that is produced within a scientist's closest community. The vastness of the scientific literature has been commonly blamed for this phenomenon, despite recent improvements in information retrieval and text mining. Its actual negative impact on scientific progress, however, has never been quantified. This analysis attempts to do so by exploring its effects on biomedical discovery, particularly in the discovery of relations between diseases, genes and chemical compounds. Results indicate that the probability that two scientific facts will enable the discovery of a new fact depends on how far apart these two facts were originally within the scientific landscape. In particular, the probability decreases exponentially with the citation distance. Thus, the direction of scientific progress is distorted based on the location in which each scientific fact is published, representing a path-dependent bias in which originally closely-located discoveries drive the sequence of future discoveries. To counter this bias, scientists should open the scope of their scientific work with modern information retrieval and extraction approaches.

Worldwide Research Trends on Diabetic Foot Ulcers (2004-2020): Suggestions for Researchers

OBJECTIVES

Diabetic foot ulcer (DFU) is one of the devastating complications of diabetes. It has high mortality and disability rates. The number of research articles on DFUs has increased. This study was designed to explore the global trends and research hotspots of DFUs to benefit researchers in shaping future research directions.

METHODS

Literatures relating to DFU from 2004 to 2020 were retrieved from the Science Citation Index Expanded (SCI-expanded) of Web of Science Core Collection (WoSCC). The current status of DFU research (including publications, journals, the performances of relevant countries, institutions, and authors and the research trends and hotspots of DFU) was analyzed with the WoSCC. VOSviewer v1.6.10.0 was utilised for cocitation, coauthorship, cooccurrence analyses, and bibliographic coupling.

RESULTS

A total of 5869 publications on DFUs were retrieved. We performed a longitudinal review of publications over 17 years: 4500 articles and 865 review articles on DFUs published from 2004 to 2020 were analyzed. The total citation was 107,296. The USA (n = 1866), England (n = 606), and China (n = 599) were the three largest contributors. The University of Washington had the greatest number of publications within this time period (n = 103), and it had the most cooperative units and was in the core position in all research institutions, followed by the University of Manchester (n = 94) and the University of Miami (n = 92). Armstrong DG (91/1.69%) and Lavery LA (55/1.19%) should be regarded as scholars who have made outstanding contributions. The top journal with the greatest total link strength was Diabetes Care. Analysis showed that the global research hotspots of DFU focused on lower limb amputation, diabetic foot infection, and treatment and management of DFU. Studies on osteomyelitis, wound therapy and management, multidisciplinary integration and mechanism of DFUs, and its related diseases are the research fronts that should be closely watched in the future.

CONCLUSIONS

This study revealed the current research status and hotspots in the domain of DFU over the past 17 years, which can help researchers to further pinpoint potential perspectives on hot topics and research frontiers.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

Depicting developing trend and core knowledge of hip fracture research: a bibliometric and visualised analysis

Background

Hip fracture is common and carries high morbidity and mortality; thus, it has become a vital concern. We aim to analyse the present status, worldwide trends in hip fracture and state of clinical research.

Methods

Publications from 2000 to 2019 were retrieved from the Web of Science database and analysed using a bibliometric methodology. VOSviewer software was utilised for analysis.

Results

In total, 6139 publications were included, and publications increased annually from 152 in 2000 to 592 in 2019. U.S. researchers have produced the most publications, the highest H-index and the greatest number of citations. Osteoporosis International has published the most papers on the topic. Leading researchers, contributing institutions, their cooperative relationships and scientific masterpieces have been identified. The publications can be divided into five clusters: ‘mortality’, ‘surgical management’, ‘rehabilitation’, ‘osteoporosis’ and ‘epidemiology’. A clear developing trend was described, which began with fracture epidemiology and prevention, transitioned to perioperative management, orthogeriatric care and patient safety and then to functional recovery, disease burden and national audits in recent times.

Conclusions

Hip fractures result in conditions that extend far beyond orthopaedics concerning epidemiology and preventive medicine, internal medicine and endocrinology, as well as critical care and gerontology. Interest, research and publications are on the rise.

The primary total knee arthroplasty: a global analysis

Background

The use of total knee arthroplasty (TKA) in treatment of chronic degenerative pathologies of the knee has boasted of an experience of 50 years. The aim of this bibliometric and visualized study is to comprehensively examine the current status and global trends of TKA research.

Methods

Publications related to TKA research from 2010 to 2019 were retrieved from Web of Science (WoS) and Science Citation Index-Expanded (SCIE) database and then analyzed through bibliometric methodology. As for the visualized study, the software VOS viewer was utilized for bibliographic coupling, coauthorship, cocitation, and co-occurrence analysis, along with further simulation of publication trends in this field.

Results

A total of 8631 publications were eventually included. The number of publications tends to increase annually worldwide. The USA was the pioneer which has made tremendous contributions, with the most publications and citations, as well as the highest H-index. The Journal of Arthroplasty has published the most papers, while Clinical Orthopaedics and Related Research has the highest citation frequency. The Hospital for Special Surgery has made the greatest contribution when total publication number and coauthorship were taken together. Studies could be divided into five clusters: “alignment study”, “revision TKA study”, “complication study”, “rehabilitation study”, and “perioperative management study”, which have a trend of balanced development in this field.

Conclusions

There will be an increasing number of publications on TKA research according to the current global trends, and the USA maintained the leadership in this area. Additionally, a trend of balanced development may exist in the field of TKA research, accompanied with inherent changes of hotspots in each cluster.

A Guide to Conquer the Biological Network Era Using Graph Theory

Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.

Soft document clustering using a novel graph covering approach

Background

In text mining, document clustering describes the efforts to assign unstructured documents to clusters, which in turn usually refer to topics. Clustering is widely used in science for data retrieval and organisation.

Results

In this paper we present and discuss a novel graph-theoretical approach for document clustering and its application on a real-world data set. We will show that the well-known graph partition to stable sets or cliques can be generalized to pseudostable sets or pseudocliques. This allows to perform a soft clustering as well as a hard clustering. The software is freely available on GitHub.

Conclusions

The presented integer linear programming as well as the greedy approach for this \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathcal {NP}$\end{document}NP-complete problem lead to valuable results on random instances and some real-world data for different similarity measures. We could show that PS-Document Clustering is a remarkable approach to document clustering and opens the complete toolbox of graph theory to this field.

Electronic supplementary material

The online version of this article (10.1186/s13040-018-0172-x) contains supplementary material, which is available to authorized users.

Multiple kernels learning-based biological entity relationship extraction method

Background

Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques.

Results

The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2–5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel.

Conclusion

In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future

"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.