The evolution of standards and data management practices in systems biology.

Mol Syst Biol. 2015 Dec 23;11(12):851

Authors: Stanford NJ, Wolstencroft K, Golebiewski M, Kania R, Juty N, Tomlinson C, Owen S, Butcher S, Hermjakob H, Le Novère N, Mueller W, Snoep J, Goble C

PMID: 26700851 [PubMed - indexed for MEDLINE]

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

Expert Rev Proteomics. 2016;13(1):99-114

Authors: Wang H, Shi T, Qian WJ, Liu T, Kagan J, Srivastava S, Smith RD, Rodland KD, Camp DG

Abstract
Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

PMID: 26581546 [PubMed - indexed for MEDLINE]

Quantification of oxidative stress phenotypes based on high-throughput growth profiling of protein kinase and phosphatase knockouts.

FEMS Yeast Res. 2016 Feb;16(1):fov101

Authors: Altıntaş A, Martini J, Mortensen UH, Workman CT

Abstract
Cellular responses to oxidative stress are important for restoring redox balance and ensuring cell survival. Genetic defects in response factors can lead to impaired response to oxidative damage and contribute to disease and aging. In single cell organisms, such as yeasts, the integrity of the oxidative stress response can be observed through its influences on growth characteristics. In this study, we investigated the time-dependent batch growth effects as a function of oxidative stress levels in protein kinase and phosphatase deletion backgrounds of Saccharomyces cerevisiae. In total, 41 different protein kinases and phosphatase mutants were selected for their known activities in oxidative stress or other stress response pathways and were investigated for their dosage-dependent response to hydrogen peroxide. Detailed growth profiles were analyzed after the induction of stress for growth rate, lag time duration and growth efficiency, and by a novel method to identify stress-induced diauxic shift delay. This approach extracts more phenotypic information than traditional plate-based methods due to the assessment of time dynamics in the time scale of minutes. With this approach, we were able to identify surprisingly diverse sensitivity and resistance patterns as a function of gene knockout.

PMID: 26564984 [PubMed - indexed for MEDLINE]

Proteomic landscape in Central and Eastern Europe: the 9th Central and Eastern European Proteomic Conference, Poznań, Poland.

Expert Rev Proteomics. 2016;13(1):5-7

Authors: Gadher SJ, Marczak Ł, Łuczak M, Stobiecki M, Widlak P, Kovarova H

Abstract
Every year since 2007, the Central and Eastern European Proteomic Conference (CEEPC) has excelled in representing state-of-the-art proteomics in and around Central and Eastern Europe, and linking it to international institutions worldwide. Its mission remains to contribute to all approaches of proteomics including traditional and often-revisited methodologies as well as the latest technological achievements in clinical, quantitative and structural proteomics with a view to systems biology of a variety of processes. The 9th CEEPC was held from June 15th to 18th, 2015, at the Institute of Bioorganic Chemistry, Polish Academy of Sciences in Poznań, Poland. The scientific program stimulated exchange of proteomic knowledge whilst the spectacular venue of the conference allowed participants to enjoy the cobblestoned historical city of Poznań.

PMID: 26558656 [PubMed - indexed for MEDLINE]

Linking Microbiota to Human Diseases: A Systems Biology Perspective.

Trends Endocrinol Metab. 2015 Dec;26(12):758-70

Authors: Wu H, Tremaroli V, Bäckhed F

Abstract
The human gut microbiota encompasses a densely populated ecosystem that provides essential functions for host development, immune maturation, and metabolism. Alterations to the gut microbiota have been observed in numerous diseases, including human metabolic diseases such as obesity, type 2 diabetes (T2D), and irritable bowel syndrome, and some animal experiments have suggested causality. However, few studies have validated causality in humans and the underlying mechanisms remain largely to be elucidated. We discuss how systems biology approaches combined with new experimental technologies may disentangle some of the mechanistic details in the complex interactions of diet, microbiota, and host metabolism and may provide testable hypotheses for advancing our current understanding of human-microbiota interaction.

PMID: 26555600 [PubMed - indexed for MEDLINE]

PPIXpress: construction of condition-specific protein interaction networks based on transcript expression.

Bioinformatics. 2016 Feb 15;32(4):571-8

Authors: Will T, Helms V

Abstract
UNLABELLED: Protein-protein interaction networks are an important component of modern systems biology. Yet, comparatively few efforts have been made to tailor their topology to the actual cellular condition being studied. Here, we present a network construction method that exploits expression data at the transcript-level and thus reveals alterations in protein connectivity not only caused by differential gene expression but also by alternative splicing. We achieved this by establishing a direct correspondence between individual protein interactions and underlying domain interactions in a complete but condition-unspecific protein interaction network. This knowledge was then used to infer the condition-specific presence of interactions from the dominant protein isoforms. When we compared contextualized interaction networks of matched normal and tumor samples in breast cancer, our transcript-based construction identified more significant alterations that affected proteins associated with cancerogenesis than a method that only uses gene expression data. The approach is provided as the user-friendly tool PPIXpress.
AVAILABILITY AND IMPLEMENTATION: PPIXpress is available at https://sourceforge.net/projects/ppixpress/.

PMID: 26508756 [PubMed - indexed for MEDLINE]

Analytical Lipidomics in Metabolic and Clinical Research.

Trends Endocrinol Metab. 2015 Dec;26(12):671-3

Authors: Hyötyläinen T, Orešič M

Abstract
Lipidomic analysis, which enables comprehensive characterization of molecular lipids in biological systems, is rapidly becoming an essential tool in biomedical research. While lipidomics already have contributed to several conceptual advances in metabolic research and led to new, validated disease biomarkers, its translation into the clinic remains a challenge.

PMID: 26439978 [PubMed - indexed for MEDLINE]

Automated Neuroanatomical Relation Extraction: A Linguistically Motivated Approach with a PVT Connectivity Graph Case Study.

Front Neuroinform. 2016;10:39

Authors: Gökdeniz E, Özgür A, Canbeyli R

Abstract
Identifying the relations among different regions of the brain is vital for a better understanding of how the brain functions. While a large number of studies have investigated the neuroanatomical and neurochemical connections among brain structures, their specific findings are found in publications scattered over a large number of years and different types of publications. Text mining techniques have provided the means to extract specific types of information from a large number of publications with the aim of presenting a larger, if not necessarily an exhaustive picture. By using natural language processing techniques, the present paper aims to identify connectivity relations among brain regions in general and relations relevant to the paraventricular nucleus of the thalamus (PVT) in particular. We introduce a linguistically motivated approach based on patterns defined over the constituency and dependency parse trees of sentences. Besides the presence of a relation between a pair of brain regions, the proposed method also identifies the directionality of the relation, which enables the creation and analysis of a directional brain region connectivity graph. The approach is evaluated over the manually annotated data sets of the WhiteText Project. In addition, as a case study, the method is applied to extract and analyze the connectivity graph of PVT, which is an important brain region that is considered to influence many functions ranging from arousal, motivation, and drug-seeking behavior to attention. The results of the PVT connectivity graph show that PVT may be a new target of research in mood assessment.

PMID: 27708573 [PubMed - in process]

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Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells.

PeerJ. 2016;4:e2478

Authors: Huang CH, Ciou JS, Chen ST, Kok VC, Chung Y, Tsai JJ, Kurubanjerdjit N, Huang CF, Ng KL

Abstract
BACKGROUND: Abnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear.
METHODS: In this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay.
RESULTS: Based on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and DrugBank resources were used to identify potential drugs and targeted genes for vascular diseases involve VSMC proliferation. Our findings are supported by in-vitro experimental IC50, binding activity data and clinical trials.
CONCLUSION: This study provides a systematic strategy to discover potential drugs and target genes, by which we hope to shed light on the treatments of VSMC proliferation associated diseases.

PMID: 27703845 [PubMed - in process]

Cystic fibrosis transmembrane conductance regulator modulators in cystic fibrosis: current perspectives.

Clin Pharmacol. 2016;8:127-140

Authors: Schmidt BZ, Haaf JB, Leal T, Noel S

Abstract
Mutations of the CFTR gene cause cystic fibrosis (CF), the most common recessive monogenic disease worldwide. These mutations alter the synthesis, processing, function, or half-life of CFTR, the main chloride channel expressed in the apical membrane of epithelial cells in the airway, intestine, pancreas, and reproductive tract. Lung disease is the most critical manifestation of CF. It is characterized by airway obstruction, infection, and inflammation that lead to fatal tissue destruction. In spite of great advances in early and multidisciplinary medical care, and in our understanding of the pathophysiology, CF is still considerably reducing the life expectancy of patients. This review highlights the current development in pharmacological modulators of CFTR, which aim at rescuing the expression and/or function of mutated CFTR. While only Kalydeco® and Orkambi® are currently available to patients, many other families of CFTR modulators are undergoing preclinical and clinical investigations. Drug repositioning and personalized medicine are particularly detailed in this review as they represent the most promising strategies for restoring CFTR function in CF.

PMID: 27703398 [PubMed - in process]

Performance of a third trimester combined screening model for the prediction of adverse perinatal outcome.

Ultrasound Obstet Gynecol. 2016 Oct 5;:

Authors: Miranda J, Triunfo S, Rodriguez-Lopez M, Sairanen M, Kouru H, Parra-Saavedra M, Crovetto F, Figueras F, Crispi F, Gratacos E

Abstract
OBJECTIVE: To explore the potential value of a third trimester combined screening for the prediction of adverse perinatal outcome (APO) in the general population and among small-for-gestational age (SGA) neonates.
METHODS: Nested case-control study within a prospective cohort of 1,590 singleton gestations referred for third-trimester evaluation (32(0) -36(6) weeks of gestation). Maternal baseline characteristics, mean arterial blood pressure, fetoplacental ultrasound and circulating biochemical markers [placental growth factor (PlGF), lipocalin-2, unconjugated estriol and inhibin A] were assessed in all women who subsequently presented an APO (n = 148) and in a control group without perinatal complications (n = 902). APO were defined by the occurrence of stillbirth, umbilical artery cord blood pH<7.15, 5 minutes Apgar score <7 or emergency operative delivery for fetal distress. Logistic regression predictive models were developed for the prediction of APO in the general population and among SGA cases (defined as customized birth weight < 10(th) centile).
RESULTS: The prevalence of APO was 9.3% in the general population and 27.4% among SGA cases. In the general population, a combined screening model including a priori risk (maternal characteristics), estimated fetal weight centile (EFW), umbilical artery pulsatility index (UA-PI), estriol and PlGF, achieves a detection rate of 26% (AUC 0.59, 95% CI 0.53-0.64) for APO, at a 10% false positive rate (FPR). Among SGA cases, the model included a priori risk, EFWc, UA-PI, cerebroplacental ratio, estriol and PlGF predicting 62% of APO [AUC 0.86 (95% CI 0.80-0.92)] at a 10% FPR.
CONCLUSIONS: The use of fetal ultrasound and maternal biochemical markers at 32-36 weeks of gestation provides a poor prediction for APO in the general population. Although continue to be limited, the performance of the screening model is improved when is applied to fetuses with suboptimal fetal growth.

PMID: 27706856 [PubMed - as supplied by publisher]

Primary immunodeficiencies : Report of 33 Pediatric Tunisian cases.

Tunis Med. 2016 Apr;94(4):320-325

Authors: Halioui-Louhaichi S, Azzabi O, Mattoussi N, Labiadh H, Bousseta K, Tebib N, Gargah T, Ben Becher S, Barbouch MR, Bejaoui M, Maherzi A

Abstract
Background Primary immunodeficiencies (PID) are a group of heterogeneous and relatively rare diseases. Aim to determine the clinical characteristics, outcome and genetic data of primary immunodeficiencies in pediatrics patients. Methods A retrospective, descriptive and multicentered study, enrolling 33 children presenting a PID in Tunis, during a period of 22 years (1991-2012). Resultats a masculine predominance has been noticed with a sex ratio at 2,3. Consanguinity was found in 71% of family cases. History of early infant deaths was found in 42% of cases. The media age of diagnosis was of 1 year 2 months. The median diagnosis delay was of 11 months and 1/2. Most frenquently observed PID were combined immunodeficiency (36%), mostly severe combined immunodeficiency (SCID) (21%), followed by congenial defects of phagocyte function (33%), mostly chronic granulomatosis disease (21%). Antibody defects were found in 21% of cases. Most frequently observed out comes were lung infections (66%) recurrent oral thrush (57%) and diarrhea (42%). Most important complications were severe infections and bronchiectasis. 30% of patients were dead by the end of the study. A molecular characterization was performed in 33% of patients, and an antenatal diagnosis was performed in 10% of cases. Conclusion The PID are a group of disease with variable expressions and etiologies. Their frequency remains understimated in Tunisia, and their management, difficult and insufficient. We suggest the establishment of systematic genetic consulting visit, the creation of a national registry and developing bone marrow transplantation in children in Tunisia.

PMID: 27704518 [PubMed - in process]

Microchip in situ electrosynthesis of silver metallic oxide clusters for ultra-FAST detection of galactose in galactosemic newborns' urine samples.

Analyst. 2016 Sep 23;:

Authors: García-Carmona L, Rojas D, González MC, Escarpa A

Abstract
This work describes for the first time the coupling of microfluidic chips (MC) to electrosynthetized silver metallic oxide clusters (AgMOCs). As an early demonstration of this novel approach, the ultrafast detection of galactose in galactosemic newborns' urine samples is proposed. AgMOCs were in situ electrosynthetized on integrated microchip platinum electrodes using a double pulse technique and characterized in full using scanning electronic microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS) and electrochemical techniques revealing the presence of silver oxides and electrocatalysis towards galactose as a galactosemia biomarker. Galactose detection in galactosemic newborns' urine samples proceeded in less than 30 s, differentiating between ill and healthy urine samples and requiring negligible urine sample consumption. The significance of the newborns' urine samples confirmed the analytical potency of the MC-AgMOCs approach for future implementation of screening for rare disease diagnosis such as galactosemia.

PMID: 27704089 [PubMed - as supplied by publisher]

Trans-ethnic meta-analysis of genome-wide association studies for Hirschsprung disease.

Hum Mol Genet. 2016 Oct 3;:

Authors: Tang CS, Gui H, Kapoor A, Kim JH, Luzón-Toro B, Pelet A, Burzynski G, Lantieri F, So MT, Berrios C, Shin HD, Fernández RM, Le TL, Verheij JB, Matera I, Cherny SS, Nandakumar P, Cheong HS, Antiñolo G, Amiel J, Seo JM, Kim DY, Oh JT, Lyonnet S, Borrego S, Ceccherini I, Hofstra RM, Chakravarti A, Kim HY, Sham PC, Tam PK, Garcia-Barceló MM

Abstract
Hirschsprung disease (HSCR) is the most common cause of neonatal intestinal obstruction. It is characterized by the absence of ganglia in the nerve plexuses of the lower gastrointestinal tract. So far, three common disease-susceptibility variants at the RET, SEMA3 and NRG1 loci have been detected through genome-wide association studies (GWAS) in Europeans and Asians to understand its genetic etiologies. Here we present a trans-ethnic meta-analysis of 507 HSCR cases and 1191 controls, combining all published GWAS results on HSCR to fine-map these loci and narrow down the putatively causal variants to 99% credible sets. We also demonstrate that the effects of RET and NRG1 are universal across European and Asian ancestries. In contrast, we detected a European-specific association of a low-frequency variant, rs80227144, in SEMA3 (odds ratio (OR)=5.2, P=4.7x10(-10)). Conditional analyses on the lead SNPs revealed a secondary association signal, corresponding to an Asian-specific, low-frequency missense variant encoding RET p.Asp489Asn (rs9282834, conditional OR=20.3, conditional P=4.1x10(-14)). When in trans with the RET intron 1 enhancer risk allele, rs9282834 increases the risk of HSCR from 1.1 to 26.7. Overall, our study provides further insights into the genetic architecture of HSCR and has profound implications for future study designs.

PMID: 27702942 [PubMed - as supplied by publisher]

Web Video Event Recognition by Semantic Analysis from Ubiquitous Documents.

IEEE Trans Image Process. 2016 Sep 27;:

Authors: Yu L, Yang Y, Huang Z, Wang P, Song J, Shen H

Abstract
In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyse video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of web video event recognition, where web videos often describe largegranular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video datasets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of web video event recognition.

PMID: 27705859 [PubMed - as supplied by publisher]

Pharmacogenomics Can Enhance Prescribing of Psychiatric Medications.

South Med J. 2016 Oct;109(10):628-630

Authors: Narang P, Johnson A, Enja M, Lippmann S

Abstract
Many psychiatric patients experience pharmaceutical intolerances, and some of them do not derive optimal efficacy from their pharmacotherapies. Clinical problems such as these may result in prolonged dysfunction, adverse consequences, and repeated changes in medication treatment regimens. Pharmacogenomics is a laboratory method that aids individualized medication selection by predicting drug efficacy and adverse effect profiles. It is a technique that involves the testing of patients' genetic makeup to improve medicinal response and tolerance. Pharmacogenomics aims to clarify pharmacokinetics and pharmacodynamics in addition to focusing on hepatic cytochrome enzyme metabolism. Ultimately, it facilitates optimal selection and adjustment of medications to enhance clinical outcomes. Pharmacogenomics is most useful in cases in which routinely prescribed pharmacotherapies are either suboptimally effective or have unacceptable adverse effects. Once there has been a failure of a therapeutic drug treatment, rather than "blindly" selecting an alternative medicine, pharmacogenomic test results can provide guidance for the selection of the most appropriate drug and its dose. The intent is to yield a greater likelihood of patient success in following a therapeutic intervention.

PMID: 27706500 [PubMed - in process]

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose.

Proc Natl Acad Sci U S A. 2016 Oct 4;:

Authors: Lever M, Lim HS, Kruger P, Nguyen J, Trendel N, Abu-Shah E, Maini PK, van der Merwe PA, Dushek O

Abstract
T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways.

PMID: 27702900 [PubMed - as supplied by publisher]

Development and validation of algorithms for the detection of statin myopathy signals from electronic medical records.

Clin Pharmacol Ther. 2016 Oct 5;:

Authors: Chan SL, Tham MY, Tan SH, Loke C, Foo B, Fan Y, Ang PS, Brunham LR, Sung C

Abstract
The aim of this study was to develop and validate sensitive algorithms to detect hospitalized statin-induced myopathy (SIM) cases from electronic medical records (EMRs). We developed 4 algorithms on a training set of 31,211 patient records from a large tertiary hospital. We determined the performance of these algorithms against manually curated records. The best algorithm used a combination of elevated creatine kinase (>4x upper limit of normal), discharge summary, diagnosis, and absence of statin in discharge medications. This algorithm achieved a positive predictive value of 52-71% and a sensitivity of 72-78% on two validation sets of >30,000 records each. Using this algorithm, the incidence of SIM was estimated at 0.18%. This algorithm captured three times more rhabdomyolysis cases than spontaneous reports (95% vs. 30% of manually curated gold standard cases). Our results show the potential power of utilizing data and text mining of EMRs to enhance pharmacovigilance activities. This article is protected by copyright. All rights reserved.

PMID: 27706800 [PubMed - as supplied by publisher]

PubMedPortable: A Framework for Supporting the Development of Text Mining Applications.

PLoS One. 2016;11(10):e0163794

Authors: Döring K, Grüning BA, Telukunta KK, Thomas P, Günther S

Abstract
Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds a relational database and a full text index on PubMed citations. It can be applied either to the complete PubMed data set or an arbitrary subset of downloaded PubMed XML files. The software provides the infrastructure to combine stand-alone applications by exporting different data formats, e.g. BioC. The presented workflows show how to use PubMedPortable to retrieve, store, and analyse a disease-specific data set. The provided use cases are well documented in the PubMedPortable wiki. The open-source software library is small, easy to use, and scalable to the user's system requirements. It is freely available for Linux on the web at https://github.com/KerstenDoering/PubMedPortable and for other operating systems as a virtual container. The approach was tested extensively and applied successfully in several projects.

PMID: 27706202 [PubMed - in process]