Background: Identification of genes that modulate longevity is a major focus of aging-related research and an area of intense public interest. In addition to facilitating an improved understanding of the basic mechanisms of aging, such genes represent potential targets for therapeutic intervention in multiple age-associated diseases, including cancer, heart disease, diabetes, and neurodegenerative disorders. To date, however, targeted efforts at identifying longevity-associated genes have been limited by a lack of predictive power, and useful algorithms for candidate gene-identification have also been lacking. Methodology/principal findings: We have utilized a shortest-path network analysis to identify novel genes that modulate longevity in Saccharomyces cerevisiae. Based on a set of previously reported genes associated with increased life span, we applied a shortest-path network algorithm to a pre-existing protein-protein interaction dataset in order to construct a shortest-path longevity network. To validate this network, the replicative aging potential of 88 single-gene deletion strains corresponding to predicted components of the shortest-path longevity network was determined. Here we report that the single-gene deletion strains identified by our shortest-path longevity analysis are significantly enriched for mutations conferring either increased or decreased replicative life span, relative to a randomly selected set of 564 single-gene deletion strains or to the current data set available for the entire haploid deletion collection. Further, we report the identification of previously unknown longevity genes, several of which function in a conserved longevity pathway believed to mediate life span extension in response to dietary restriction. Conclusions/significance: This work demonstrates that shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity and represents the first application of network analysis of aging to be extensively validated in a biological system. The novel longevity genes identified in this study are likely to yield further insight into the molecular mechanisms of aging and age-associated disease.
Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems. Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production. It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models.
Microarray technology allows for high throughput gene expression studies. However, because of the large amounts of data produced, additional work is required to put the data into biological context. An emerging approach to provide such context is pathway and network analysis. The objective of this work was to design and implement such pathway analysis strategies. Our strategy identifies enriched biological pathways when given a list of genes found to be differentially expressed in a microarray experiment. Once enriched pathways are identified, our strategy generates scores to identify how significant and functional the identified pathways are. These scores include statistical significance and unique graph theory scores such as pathway port connectedness, adjacency ratio, and completeness. Enzyme-centric scores are also generated to quantify the importance of each enzyme-coding gene in the pathway it participates in. Pathways in other organisms are inferred based on homology and several methods of visualizing the pathways are also provided. This approach can also be extended to proteomic data, or comparative genomic data to assess the relevance of a pathway or network in an organism or group of organisms.
Macromolecular mechanisms of the cell are shaped by evolutionary pro-cesses, and so are biological networks. These networks, sum of all the interactions between cellular components, are used as a convenient repre-sentation of the cell's internal organization. From the structure of these networks one can derive general principles of this organization. What is missing, however, is the precise knowledge of how this organization is linked to the phylogeny of species. We present here examples of our work to characterize this link. In the first part we introduce an intuitive and robust description of the metabolic capabilities of species, termed net-work of interacting pathways or NIP. In the second part, we show that NIPs capture sufficient information about the underlying evolutionary events leading to the formation of metabolic networks to permit accurate prediction of the phylogenetic position of species.
Conference: Proceedings of the conference MOL2NET International Conference on Multidisciplinary Sciences (4th edition), 2018 is part of a year-round worldwide conference series hosted by MDPI Sciforum, Basel, Switzerland. This conference series has had organized more than 20 associated workshop series in universities worldwide: USA, France, Portugal, Spain, China, Chile, Brazil, India, etc. These workshop series run in person and/or online. Some of these workshops are the SRI-10 St Thomas University (STU)- Miami Dade College (MDC), Miami, USA; USINEWS-02 University of Minnesota, USA; BIOCHEMPHYS-01 CNAM, Paris, France; WCUCW, West Coast University, Miami, USA; IWMEDIC UDC, Coruña, Spain, LAWSCI-02, UPV/EHU, Bilbao, Spain, etc. Workshops allow both in person and/or online only publication of papers, research highlights of previous papers, letters, short reviews, etc. Topics: The topics are multidisciplinary covering, but not limited to, Chemistry (All areas), Physics, Biology, Ecology, Statistics, Bioinformatics, Education, Nanotechnology, Materials, Computational, Complex Networks, Legal, and Social sciences, etc. Statistics: This edition hosted >10 workshops that attracted >300 communications submitted by >700 authors. We organized 7 special issues published in JCR journals (MDPI editorial) such as Molecules, Entropy, and Appl. Sci. We also organized 3 bootcamps, hand-training, or capstone courses in MDC, Miami, WCU Miami, and UPV/EHU Bilbao. The present book of proceedings have released in two versions; one with 94 pages (short version without communications) and other with 2985 pages (long version including all communications and abstracts). Thank you very much to all colleagues for your kind support.
Although metabolic reactions are unquestionably shaped by evolutionary processes, the degree to which the overall structure and complexity of their interconnections are linked to the phylogeny of species has not been evaluated in depth. Here, we apply an original metabolome representation, termed Network of Interacting Pathways or NIP, with a combination of graph theoretical and machine learning strategies, to address this question. NIPs compress the information of the metabolic network exhibited by a species into much smaller networks of overlapping metabolic pathways, where nodes are pathways and links are the metabolites they exchange. Our analysis shows that a small set of descriptors of the structure and complexity of the NIPs combined into regression models reproduce very accurately reference phylogenetic distances derived from 16S rRNA sequences (10-fold cross-validation correlation coefficient higher than 0.9). Our method also showed better scores than previous work on metabolism-based phylogenetic reconstructions, as assessed by branch distances score, topological similarity and second cousins score. Thus, our metabolome representation as network of overlapping metabolic pathways captures sufficient information about the underlying evolutionary events leading to the formation of metabolic networks and species phylogeny. It is important to note that precise knowledge of all of the reactions in these pathways is not required for these reconstructions. These observations underscore the potential for the use of abstract, modular representations of metabolic reactions as tools in studying the evolution of species. Supplementary data are available at Bioinformatics online.
The complex interactions that characterize acute wound healing have stymied the development of effective therapeutic modalities. The use of computational models holds the promise to improve our basic approach to understanding the process. By modifying an existing ordinary differential equation model of systemic inflammation to simulate local wound healing, we expect to improve the understanding of the underlying complexities of wound healing and thus allow for the development of novel, targeted therapeutic strategies. The modifications in this local acute wound healing model include: evolution from a systemic model to a local model, the incorporation of fibroblast activity, and the effects of tissue oxygenation. Using these modifications we are able to simulate impaired wound healing in hypoxic wounds with varying levels of contamination. Possible therapeutic targets, such as fibroblast death rate and rate of fibroblast recruitment, have been identified by computational analysis. This model is a step toward constructing an integrative systems biology model of human wound healing.
There are many parasite species with very different antiparasite drugs susceptibility. Computational methods in biology and chemistry prediction of the biological activity based on Quantitative Structure-Activity Relationships (QSAR) susbtantialy increases the potentialities of this kind of networks avoiding time and resources consming experiments. Unfortunately, almost QSAR models are unspecific or predict activity against only one species. To solve this problem we developed here a multi-species QSAR classification model (ms-QSAR). In so doing, we use Markov Chains theory to calculate new multi-target spectral moments to fit a QSAR model that predict by the first time a ms-QSAR model for 500 drugs tested in the literature against 16 parasite species and other 207 drugs no tested in the literature using entropy type indices. The data was processed by Artificial Neural Network (ANN) classifying drugs as active or non-active against the different tested parasite species. The best ANN found was MLP 23:23-18-1:1. Overall model classification accuracy was 85.65% (211/244 cases) in training. Validation of the model was carried out by means of external predicting series. In this serie, the model classified correctly 81.85% (275/357 cases).
The etiologic basis for sporadic forms of neurodegenerative diseases has been elusive but likely represents the product of genetic predisposition and various environmental factors. Specific gene-environment interactions have become more salient owing, in part, to the elucidation of epigenetic mechanisms and their impact on health and disease. The linkage between traumatic brain injury (TBI) and Parkinson's disease (PD) is one such association that currently lacks a mechanistic basis. Herein, we present preliminary blood-based metabolomic evidence in support of potential association between TBI and PD. Using untargeted and targeted high-performance liquid chromatography-mass spectrometry we identified metabolomic biomarker profiles in a cohort of symptomatic mild TBI (mTBI) subjects (n = 75) 3-12 months following injury (subacute) and TBI controls (n = 20), and a PD cohort with known PD (n = 20) or PD dementia (PDD) (n = 20) and PD controls (n = 20). Surprisingly, blood glutamic acid levels in both the subacute mTBI (increased) and PD/PDD (decreased) groups were notably altered from control levels. The observed changes in blood glutamic acid levels in mTBI and PD/PDD are discussed in relation to other metabolite profiling studies. Should our preliminary results be replicated in comparable metabolomic investigations of TBI and PD cohorts, they may contribute to an "excitotoxic" linkage between TBI and PD/PDD.
Liposomes have long been effective delivery vehicles for transport of toxins to peripheral cancers. The combination of convection-enhanced delivery (CED) with liposomal toxins was originally proposed to circumvent the limited delivery of intravascular liposomes to the central nervous system (CNS) due to the blood-brain-barrier (BBB). CED offers markedly improved distribution of infused therapeutics within the CNS compared to direct injection or via drug eluting polymers, both of which depend on diffusion for parenchymal distribution. This review examines the basis for improved delivery of liposomal toxins via CED within the CNS, and discusses preclinical and clinical experience with these therapeutic techniques. How CED and liposomal technologies may influence future neurooncologic treatments are also considered.
MOL2NET is an international conference to promote interdisciplinary synergies in science. The confrence is totally online. The conference is being hosted by the site SciForum; a platform of the editorial MDPI, Basel, Switzerland. The main emphasis is to promote collaborations between Experimental Molecular and Biomedical Sciences with Computer, Data, and Network Science experts. We invite you to send short communications (1-3 pages) or research papers (not page limits). You can send papers with: (1) experimental research only, (2) theoretical papers, (3) papers combining experimental and theoretical methods, (4) papers discussing legal aspects of interdisciplinary research. Please use the present .doc file as template to send papers to our conference. Registration and Publications is totally free, the submission of paper is online using the following link: http://sciforum.net/user/submission_for_conference/83
This year the MOL2NET is the online host conference for IWMEDIC-04 (see details on Section I). IWMEDIC-04 is the IV International Workshop on Medical Imaging, Medical Coding, and Clinical Data Analysis of University of Coruña (UDC). The IWMEDIC-04 workshop will be held presentially at the University Hospital Complex of A Coruña (June, 20, 2016), Hospital Médico Quirúrgico San Rafael (June, 21,2016), and Faculty of Computer Sciences, UDC (June, 20-22, 2016). The chairman of this workshop is Prof. Alejandro Pazos; Ph.D., M.D., Chair and Director of Department of Computer Sciences, UDC, Coruña, Spain. The topics include, but are not limited to, Medical Imaging Processing, Medical Informatics, Medical Coding, Bioinformatics, Computer Aided Drug Desing, Data Analysis, etc. English will be the official language for online publication and presentations, as per MDPI rules, presential lectures may be in English, Spanish, or Galician.
CONFERENCE SERIES CALL FOR PAPERS We are glad to invite all colleagues worldwide to participate on the MOL2NET International Conference Series on Multidisciplinary Sciences. MOL2NET (the conference running title) is the acronym of the lemma of the conference: From Molecules to Networks. This running title is inspired by the possibility of multidisciplinary collaborations in science between experimental and theoretical scientists. Homepage (2017 edition): http://sciforum.net/conference/mol2net-03. This is an International Conference Series to Foster Interdisciplinary Collaborations in Sciences with emphasis on Experimental Chemistry (all branches), Materials Science, Nanotechnology, Life Sciences, Medicine, and Healthcare, along with Data Analysis, Computer Sciences, Bioinformatics, Systems Biology, and Complex Networks Sciences. The Scientific Headquarters (HQs) of this conference series are in the Faculty of Science and Technology, University of Basque Country (UPV/EHU), Biscay, Spain. However, the idea of this multidisciplinary conference emerged from the melting pot formed as the result of multiple collaborations of professors of IKERBASQUE, Basque Foundation for Sciences, the two departments Department of Organic Chemistry I and Department of Organic Chemistry II of the University of Basque Country UPV/EHU, the Department of Computer Sciences of the University of Coruña (UDC), the Center for the Study of Biological Complexity of the Virginia Commonwealth University (VCU), USA, and many other institutions. Aims & Scope: It is devoted to the development of an online conference with a network of face-to-face (in person) associated workshops in different countries (USA, Spain, China, India, Brasil, etc.) linked and published online by a Sciforum conference platform (open access but free of charge) and special issues in MDPI journals with JCR impact factor (open access) in order to promote multidisciplinary education and collaborations in science (Chemistry, Applied Physics, Data Science, Computer Science, Nanotechnology, Medicine, Bio-sciences, etc.) between senior and young researchers worldwide. Collaborators: We listed as collaborators some members of the committee of the first edition (2015) with active Research Gate accounts, see welcome message and full committee list here: http://sciforum.net/conference/mol2net-02 Workshops Details: Face-to-Face Associated Workshops (in person) developed or under development (until now) in USA, Spain, China, India, Brazil, etc., see details on Google page: http://bit.do/google-mol2net-workshops List of Workshops: SRI-08: The 8th Annual Undergraduate Summer Research Symposium of Saint Thomas University, Miami, USA, Sept, 2016. Symposium of the Summer Research Institute (SRI), HQ, St. Thomas University (STU), http://sciforum.net/conference/mol2net-02/sri-08 UFIQOSYC 1st Young Scientist Workshop, Department of Organic Chemistry II, Universidad del País Vasco / Euskal Herriko Unibertsitatea, Leioa, Vizcaya, Spain. http://sciforum.net/conference/mol2net-02/ufi-qosyc SUIWCS-01, Soochow University International Workshop Series on Computer Sciences (see details on Section J). SUIWCS-01 workshop of School of Computer Science and Technology of Soochow University (PRC), Suzhou, China. http://sciforum.net/conference/mol2net-02/suiwml-01 IWMEDIC-04, IV International Workshop on Medical Imaging, Medical Coding, and Clinical Data Analysis of University of A Coruña (UDC). Chairperson: Prof. Alejandro Pazos. http://sciforum.net/conference/mol2net-02/iwmedic-04 WRSAMC2016: Workshop in Research Sciences Applied to Medicinal Chemistry, PNSB, Universidade Federal da Paraíba, Brasil, http://sciforum.net/conference/mol2net-02/wrsamc-01 CIESABIO 2016, Workshop on Biotechnology and Zoonotic Diseases of CIESA, FMVZ, UAEMEX Universidad Atónoma del Estado de México (UAEM). Chairperson. http://sciforum.net/conference/mol2net-02/ciesabio-01 MODEC2016 workshop of Universidad Estatal Amazónica on the development of natural products and agroindustrial process in Ecuador Amazon regions. The workshop runs both online and in person. http://sciforum.net/conference/mol2net-02/modec-01 BIOTALCA01: Workshop on Bioinformatics and Molecular Simulation, University of Talca, Chile. http://sciforum.net/conference/mol2net-02/biotalca01 Special Issues: MDPI JCR journals publish selected papers in special issues guest-edited by members of the committee: http://bit.do/ijms-mol2net-01. Languages Initiative: This international science conference focus on multidisciplinary sciences: http://sciforum.net/conference/mol2net-02. The official working language is English however we have an initiative to promote the use of other languages in order to reach non-English speakers and show the cultural heritage of different people in the world. One action in this sense includes the compilation of a playlist with welcome videos of different scientist talking about both the conference and their own work in Hindi (हिन्दी), Chinese Mandarin (官话), Spanish, French, Portuguese, and very specially in Euskera a very ancient Europe language from Basque Country (Euskadi), used today. Do not hesitate to contact Prof. Gonzalez-Diaz H. (conference ch.) email@example.com, if you want to publish a similar video introducing both the conference and your own work in English or other language. Please, watch the current playlist in Youtube: http://bit.do/mol2net-youtube How to collaborate: You are invited to: (1) participate online 1-2 pages communications (no cost), (2) assist to workshops, and/or (3) send a proposal to organize a your own associated workshop with students of your university (PhD, MSc, Degree), etc., (4) send a video for our language ininitiative, and/or (5) follow the conference on social networks like: Twitter @mol2net, Facebook group (>10000 followers): https://www.facebook.com/groups/chembioinfo.networks/ Contact: Gonzalez-Diaz H., IKERBASQUE Professor, University of The Basque Country (UPV/EHU), firstname.lastname@example.org Spanish Notes: MOL2NET, Conferencia Internacional en Ciencias Multidisciplinares, MDPI, Sciforum, Suiza, Instituciones: IKERBASQUE Fundación Vasca de Ciencia y Universidad del País Vasco (UPV/EHU), participacion online sin costo. Página oficial: http://sciforum.net/conference/mol2net-02, con workshops asociados (presenciales) http://bit.do/mol2net-workshops en varios paises. Les invitamos a: (1) participar online comunicaiones 1-2 páginas (sin coste alguno), (2) asistir a los workshops, (3) organizar workshop propio, y/o (4) ser miembros de nuestro grupo, contacto: email@example.com The MOL2NET Committee