Target identification in biological systems using network connectivity information from literature mining databases

2010 ◽  
Vol 43 (5) ◽  
pp. 91-96
Author(s):  
Ugur Guner ◽  
Jay H. Lee ◽  
Omar L. Francone ◽  
Dmitriy Leyfer
Keyword(s):  
Target Identification ◽  
Biological Systems ◽  
Network Connectivity ◽  
Literature Mining ◽  
Connectivity Information

scholarly journals Deep Proteome Profiling Enabled Functional Annotation and Data-Independent Quantification of Proline Hydroxylation Targets

2022 ◽  
Author(s):  
Yao Gong ◽  
Gaurav Behera ◽  
Luke Erber ◽  
Ang Luo ◽  
Yue Chen
Keyword(s):  
Protein Interactions ◽  
Critical Role ◽  
Network Connectivity ◽  
Integrated Analysis ◽  
Literature Mining ◽  
Structure Stability ◽  
Proteome Profiling ◽  
Specific Distribution ◽  
Functional Features ◽  
Proline Hydroxylation

Proline hydroxylation (Hyp) regulates protein structure, stability and protein-protein interaction and is widely involved in diverse metabolic and physiological pathways in cells and diseases. To reveal functional features of the proline hydroxylation proteome, we integrated various data sources for deep proteome profiling of proline hydroxylation proteome in human and developed HypDB (https://www.HypDB.site), an annotated database and web server for proline hydroxylation proteome. HypDB provides site-specific evidence of modification based on extensive LC-MS analysis and literature mining with 15319 non-redundant Hyp sites and 8226 sites with high confidence on human proteins. Annotation analysis revealed significant enrichment of proline hydroxylation on key functional domains and tissue-specific distribution of Hyp abundance across 26 types of human organs and fluids and 6 cell lines. The network connectivity analysis further revealed a critical role of proline hydroxylation in mediating protein-protein interactions. Moreover, the spectral library generated by HypDB enabled data-independent analysis (DIA) of clinical tissues and the identification of novel Hyp biomarkers in lung cancer and kidney cancer. Taken together, our integrated analysis of human proteome with publicly accessible HypDB revealed functional diversity of Hyp substrates and provides a quantitative data source to characterize proline hydroxylation in pathways and diseases.

scholarly journals Literature Evidence in Open Targets – a target validation platform

2017 ◽  
Author(s):  
Şenay Kafkas ◽  
Ian Dunham ◽  
Johanna McEntyre
Keyword(s):  
Drug Target ◽  
Target Identification ◽  
Relevant Literature ◽  
Literature Mining ◽  
Target Validation ◽  
Link Type ◽  
Drug Target Identification ◽  
Disease Associations ◽  
Target Disease ◽  
Literature Evidence

AbstractBackgroundWe present the Europe PMC literature component of Open Targets – a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confidence from the Europe PMC literature database, by using rules utilising expert-provided heuristic information and serves the platform regularly with the up-to-date data since December, 2015.ResultsCurrently, there are a total number of 1168365 distinct target-disease associations text mined from >26 million PubMed abstracts and >1.2 million Open Access full text articles. Our comparative analyses on the current available evidence data in the platform revealed that 850179 of these associations are exclusively identified by literature mining.ConclusionThis component helps the platform’s users by providing the most relevant literature hits for a given target and disease. The text mining evidence along with the other types of evidence can be explored visually through https://www.targetvalidation.org and all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data.

scholarly journals Revealing the Interactions Between Diabetes, Diabetes-Related Diseases, and Cancers Based on the Network Connectivity of Their Related Genes

2020 ◽  
Vol 11 ◽  
Author(s):  
Lijuan Zhu ◽  
Ju Xiang ◽  
Qiuling Wang ◽  
Ailan Wang ◽  
Chao Li ◽  
...  
Keyword(s):  
System Development ◽  
Characteristic Curve ◽  
Gene List ◽  
Network Connectivity ◽  
Literature Mining ◽  
Disease Genes ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Disease Related Genes

Diabetes-related diseases (DRDs), especially cancers pose a big threat to public health. Although people have explored pathological pathways of a few common DRDs, there is a lack of systematic studies on important biological processes (BPs) connecting diabetes and its related diseases/cancers. We have proposed and compared 10 protein–protein interaction (PPI)-based computational methods to study the connections between diabetes and 254 diseases, among which a method called DIconnectivity_eDMN performs the best in the sense that it infers a disease rank (according to its relation with diabetes) most consistent with that by literature mining. DIconnectivity_eDMN takes diabetes-related genes, other disease-related genes, a PPI network, and genes in BPs as input. It first maps genes in a BP into the PPI network to construct a BP-related subnetwork, which is expanded (in the whole PPI network) by a random walk with restart (RWR) process to generate a so-called expanded modularized network (eMN). Since the numbers of known disease genes are not high, an RWR process is also performed to generate an expanded disease-related gene list. For each eMN and disease, the expanded diabetes-related genes and disease-related genes are mapped onto the eMN. The association between diabetes and the disease is measured by the reachability of their genes on all eMNs, in which the reachability is estimated by a method similar to the Kolmogorov–Smirnov (KS) test. DIconnectivity_eDMN achieves an area under receiver operating characteristic curve (AUC) of 0.71 for predicting both Type 1 DRDs and Type 2 DRDs. In addition, DIconnectivity_eDMN reveals important BPs connecting diabetes and DRDs. For example, “respiratory system development” and “regulation of mRNA metabolic process” are critical in associating Type 1 diabetes (T1D) and many Type 1 DRDs. It is also found that the average proportion of diabetes-related genes interacting with DRDs is higher than that of non-DRDs.

Transmission Electron Microscopy of Protein Macromolecules

1971 ◽  
Vol 29 ◽  
pp. 424-425
Author(s):  
Henry S. Slayter
Keyword(s):  
Biological Systems ◽  
Metal Vapor ◽  
Resolving Power ◽  
Electron Microscopic ◽  
Chemical Methods ◽  
Molecular Weights ◽  
The Past ◽  
Physical Chemical ◽  
Transmission Electron

Electron microscopic methods have been applied increasingly during the past fifteen years, to problems in structural molecular biology. Used in conjunction with physical chemical methods and/or Fourier methods of analysis, they constitute powerful tools for determining sizes, shapes and modes of aggregation of biopolymers with molecular weights greater than 50, 000. However, the application of the e.m. to the determination of very fine structure approaching the limit of instrumental resolving power in biological systems has not been productive, due to various difficulties such as the destructive effects of dehydration, damage to the specimen by the electron beam, and lack of adequate and specific contrast. One of the most satisfactory methods for contrasting individual macromolecules involves the deposition of heavy metal vapor upon the specimen. We have investigated this process, and present here what we believe to be the more important considerations for optimizing it. Results of the application of these methods to several biological systems including muscle proteins, fibrinogen, ribosomes and chromatin will be discussed.

Freeze-fracture cytochemistry: A goal set by Russell Steere in 1957

1993 ◽  
Vol 51 ◽  
pp. 60-61
Author(s):  
Nicholas J Severs
Keyword(s):  
Chemical Nature ◽  
Biological Systems ◽  
Freeze Fracture ◽  
Structural Components ◽  
Major Goal ◽  
Membrane Biology ◽  
Routine Application ◽  
The Future ◽  
Freeze Etching

In his pioneering demonstration of the potential of freeze-etching in biological systems, Russell Steere assessed the future promise and limitations of the technique with remarkable foresight. Item 2 in his list of inherent difficulties as they then stood stated “The chemical nature of the objects seen in the replica cannot be determined”. This defined a major goal for practitioners of freeze-fracture which, for more than a decade, seemed unattainable. It was not until the introduction of the label-fracture-etch technique in the early 1970s that the mould was broken, and not until the following decade that the full scope of modern freeze-fracture cytochemistry took shape. The culmination of these developments in the 1990s now equips the researcher with a set of effective techniques for routine application in cell and membrane biology.Freeze-fracture cytochemical techniques are all designed to provide information on the chemical nature of structural components revealed by freeze-fracture, but differ in how this is achieved, in precisely what type of information is obtained, and in which types of specimen can be studied.

Seeking to uncover biology's chemical roots

2019 ◽  
Vol 3 (5) ◽  
pp. 435-443 ◽  
Author(s):  
Addy Pross
Keyword(s):  
Environmental Changes ◽  
Biological Systems ◽  
Significant Development ◽  
The Road ◽  
Physical Chemical ◽  
Systems Chemistry ◽  
Biological World ◽  
Inanimate Matter ◽  
The Origin Of Life ◽  
Opening Up

Despite the considerable advances in molecular biology over the past several decades, the nature of the physical–chemical process by which inanimate matter become transformed into simplest life remains elusive. In this review, we describe recent advances in a relatively new area of chemistry, systems chemistry, which attempts to uncover the physical–chemical principles underlying that remarkable transformation. A significant development has been the discovery that within the space of chemical potentiality there exists a largely unexplored kinetic domain which could be termed dynamic kinetic chemistry. Our analysis suggests that all biological systems and associated sub-systems belong to this distinct domain, thereby facilitating the placement of biological systems within a coherent physical/chemical framework. That discovery offers new insights into the origin of life process, as well as opening the door toward the preparation of active materials able to self-heal, adapt to environmental changes, even communicate, mimicking what transpires routinely in the biological world. The road to simplest proto-life appears to be opening up.

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