Biological Networks for Cancer Candidate Biomarkers Discovery

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

doi:10.4137/cin.s39458

Cited by 17 publications

(13 citation statements)

References 91 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This conclusion may be the result of an identification name for identification name comparison, which could miss functional connections. In a living system, different genes, transcripts as well as proteins work in a cooperative way to ensure functional responses [5,6]. Therefore, different genes and proteins may have a similar functional output.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Intersection Between Genes Controlling Vascularization and Angiogenesis in Renal Cell Carcinomas

Souchelnytskyi¹

2018

Exp. Onc.

View full text Add to dashboard Cite

Aim: To show that application of the systemic analysis may significantly improve comparison of different datasets. Different genes and proteins may converge on the same functional outputs. A comparison of 2 datasets by only identification names of affected molecules may miss that, leading to a conclusion that there is nothing in common for these datasets. Systemic analysis may overcome this limitation, by focusing on functions represented by the identification names. Materials and Methods: Datasets were retrieved from open sources. Systemic analysis of vascularization features and angiogenesis signature was performed by using Cytoscape and its plugs-in. Results: In contrary to the initial statement of the lack of overlap between the vascularization features and the angiogenesis genes-signature in renal carcinomas, we observed an intersection on the functional level. Analysis of the networks built with identification names of vascularization and angiogenesis datasets showed an intersection, which included potent regulators of vessel formation and growth. Conclusion: Analysis of networks may expose functional links, which may be missed by a direct identification names comparison.

show abstract

mentioning

confidence: 99%

“…Therefore, different genes and proteins may have a similar functional output. Such functional connections would be unveiled by a systemic analysis [5][6][7][8]. Systemic analysis focuses on affected functions rather than on identification names, and may lead to better clinically relevant conclusions.…”

mentioning

confidence: 99%

Intersection Between Genes Controlling Vascularization and Angiogenesis in Renal Cell Carcinomas

Souchelnytskyi¹

2018

Exp. Onc.

View full text Add to dashboard Cite

show abstract

“…An miRNA-gene network of L. longipalpis was constructed using Cytoscape (Kohl, Wiese & Warscheid, 2011). Topology analysis of the network identified biomarkers in the protein-protein interaction network of disease (Yan et al., 2016). The nodes and edges of the miRNA-gene network were then analyzed.…”

Section: Methodsmentioning

confidence: 99%

Improved annotation of Lutzomyia longipalpis genome using bioinformatics analysis

Yang

2019

PeerJ

View full text Add to dashboard Cite

Lutzomyia longipalpis, a sand fly, is a vector-spreading pathogenic protozoan in the New World. MicroRNA (miRNA) is evolutionarily-conserved non-coding RNA, which plays critical roles in various biological processes. To date, the functions of most proteins in L. longipalpis are unknown, and few studies have addressed the roles of miRNAs in this species. In the present study, we re-annotated the protein-coding genes and identified several miRNAs using a set of comparative genomics tools. A large number of L. longipalpis proteins were found to be homologous with those in the mosquito genome, indicating that they may have experienced similar selective pressures. Among these proteins, a set of 19 putative salivary proteins were identified, which could be used for studying the transmission of Leishmania. Twenty-one novel miRNAs were characterized, including two miRNAs, miR-4113-5p and miR-5101, which are unique to L. longipalpis. Many of the targets of these two genes were found to be involved in ATP hydrolysis-coupled proton transport, suggesting that they may have important roles in the physiology of energy production. Topology analysis of the miRNA-gene network indicated that miR-9388-5p and miR-3871-5p regulate several critical genes in response to disease development. In conclusion, our work provides a basis for improving the genome annotation of L. longipalpis, and opens a new door to understanding the molecular regulatory mechanisms in this species.

show abstract

“…Biomarkers have been used as input information in artificial neural networks for establishing cancer types and the respective malignancy (see e.g., [10,154,155]). Image fusion techniques have also been used for developing three-dimensional maps of therapeutic doses [156].…”

Section: Mapping Multidimensional Cancer Datamentioning

confidence: 99%

“…However, literature regarding cancer theranostics is lacking in comprehensive and systematic approaches to: (1) fully inspect the relevant interaction patterns and synergistic effects, (2) evaluate tumor heterogeneity and data-intensive theranostics technologies, (3) confirm the effectiveness of therapeutics, and (4) compare and validate specific mechanistic models. Fundamental aspects on the cellular and molecular basis of cancer have also been explored through the establishment of relevant biological networks [9,10,11,12,13,14,15,16,17]. This has been facilitated by combining information from cancer genomic, transcriptomic, proteomic, and metabolomic data and computational techniques, aiming at developing non-invasive methods for diagnostic purposes [9].…”

Section: Introductionmentioning

confidence: 99%

Computational Approaches in Theranostics: Mining and Predicting Cancer Data

2019

View full text Add to dashboard Cite

The ability to understand the complexity of cancer-related data has been prompted by the applications of (1) computer and data sciences, including data mining, predictive analytics, machine learning, and artificial intelligence, and (2) advances in imaging technology and probe development. Computational modelling and simulation are systematic and cost-effective tools able to identify important temporal/spatial patterns (and relationships), characterize distinct molecular features of cancer states, and address other relevant aspects, including tumor detection and heterogeneity, progression and metastasis, and drug resistance. These approaches have provided invaluable insights for improving the experimental design of therapeutic delivery systems and for increasing the translational value of the results obtained from early and preclinical studies. The big question is: Could cancer theranostics be determined and controlled in silico? This review describes the recent progress in the development of computational models and methods used to facilitate research on the molecular basis of cancer and on the respective diagnosis and optimized treatment, with particular emphasis on the design and optimization of theranostic systems. The current role of computational approaches is providing innovative, incremental, and complementary data-driven solutions for the prediction, simplification, and characterization of cancer and intrinsic mechanisms, and to promote new data-intensive, accurate diagnostics and therapeutics.

show abstract

Biological Networks for Cancer Candidate Biomarkers Discovery

Cited by 17 publications

References 91 publications

Intersection Between Genes Controlling Vascularization and Angiogenesis in Renal Cell Carcinomas

Intersection Between Genes Controlling Vascularization and Angiogenesis in Renal Cell Carcinomas

Improved annotation of Lutzomyia longipalpis genome using bioinformatics analysis

Computational Approaches in Theranostics: Mining and Predicting Cancer Data

Contact Info

Product

Resources

About