Reflection of successful anticancer drug development processes in the literature.

Drug Discov Today. 2016 Jul 18;

Authors: Heinemann F, Huber T, Meisel C, Bundschus M, Leser U

Abstract
The development of cancer drugs is time-consuming and expensive. In particular, failures in late-stage clinical trials are a major cost driver for pharmaceutical companies. This puts a high demand on methods that provide insights into the success chances of new potential medicines. In this study, we systematically analyze publication patterns emerging along the drug discovery process of targeted cancer therapies, starting from basic research to drug approval-or failure. We find clear differences in the patterns of approved drugs compared with those that failed in Phase II/III. Feeding these features into a machine learning classifier allows us to predict the approval or failure of a targeted cancer drug significantly better than educated guessing. We believe that these findings could lead to novel measures for supporting decision making in drug development.

PMID: 27443674 [PubMed - as supplied by publisher]

A literature-driven method to calculate similarities among diseases.

Comput Methods Programs Biomed. 2015 Nov;122(2):108-22

Authors: Kim H, Yoon Y, Ahn J, Park S

Abstract
BACKGROUND: "Our lives are connected by a thousand invisible threads and along these sympathetic fibers, our actions run as causes and return to us as results". It is Herman Melville's famous quote describing connections among human lives. To paraphrase the Melville's quote, diseases are connected by many functional threads and along these sympathetic fibers, diseases run as causes and return as results. The Melville's quote explains the reason for researching disease-disease similarity and disease network. Measuring similarities between diseases and constructing disease network can play an important role in disease function research and in disease treatment. To estimate disease-disease similarities, we proposed a novel literature-based method.
METHODS AND RESULTS: The proposed method extracted disease-gene relations and disease-drug relations from literature and used the frequencies of occurrence of the relations as features to calculate similarities among diseases. We also constructed disease network with top-ranking disease pairs from our method. The proposed method discovered a larger number of answer disease pairs than other comparable methods and showed the lowest p-value.
CONCLUSIONS: We presume that our method showed good results because of using literature data, using all possible gene symbols and drug names for features of a disease, and determining feature values of diseases with the frequencies of co-occurrence of two entities. The disease-disease similarities from the proposed method can be used in computational biology researches which use similarities among diseases.

PMID: 26212477 [PubMed - indexed for MEDLINE]

10 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/22

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/22

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

DESM: portal for microbial knowledge exploration systems.

Nucleic Acids Res. 2016 Jan 4;44(D1):D624-33

Authors: Salhi A, Essack M, Radovanovic A, Marchand B, Bougouffa S, Antunes A, Simoes MF, Lafi FF, Motwalli OA, Bokhari A, Malas T, Amoudi SA, Othum G, Allam I, Mineta K, Gao X, Hoehndorf R, C Archer JA, Gojobori T, Bajic VB

Abstract
Microorganisms produce an enormous variety of chemical compounds. It is of general interest for microbiology and biotechnology researchers to have means to explore information about molecular and genetic basis of functioning of different microorganisms and their ability for bioproduction. To enable such exploration, we compiled 45 topic-specific knowledgebases (KBs) accessible through DESM portal (www.cbrc.kaust.edu.sa/desm). The KBs contain information derived through text-mining of PubMed information and complemented by information data-mined from various other resources (e.g. ChEBI, Entrez Gene, GO, KOBAS, KEGG, UniPathways, BioGrid). All PubMed records were indexed using 4,538,278 concepts from 29 dictionaries, with 1 638 986 records utilized in KBs. Concepts used are normalized whenever possible. Most of the KBs focus on a particular type of microbial activity, such as production of biocatalysts or nutraceuticals. Others are focused on specific categories of microorganisms, e.g. streptomyces or cyanobacteria. KBs are all structured in a uniform manner and have a standardized user interface. Information exploration is enabled through various searches. Users can explore statistically most significant concepts or pairs of concepts, generate hypotheses, create interactive networks of associated concepts and export results. We believe DESM will be a useful complement to the existing resources to benefit microbiology and biotechnology research.

PMID: 26546514 [PubMed - indexed for MEDLINE]

Explicit Drug Re-positioning: Predicting Novel Drug-Target Interactions of the Shelved Molecules with QM/MM Based Approaches.

Adv Protein Chem Struct Biol. 2015;100:89-112

Authors: Omer A, Suryanarayanan V, Selvaraj C, Singh SK, Singh P

Abstract
With the demand to enhance the speed of the drug discovery process there has been an increased usage of computational approaches in drug discovery studies. However because of their probabilistic outcomes, the challenge is to exactly mimic the natural environment which can provide the exact charge polarization effect while estimating the binding energy between protein and ligand. There has been a large number of scoring functions from simple one to the complex one available for estimating binding energy. The quantum mechanics/molecular mechanics (QM/MM) hybrid approach has been the preferred choice of interest since last decade for modeling reactions in biomolecular systems. The application of QM/MM approach has been expanded right from rescoring the already known complexes and depicting the correct position of some novel molecule to ranking a large number of molecules. It is expected that the application of QM/MM-based scoring will grow in all areas of drug discovery. However, the most promising area will be its application in repositioning, that is, assigning novel functions or targets to the already existing drugs, as this would stop the rising attrition rates as well as reduce the overall time and cost of drug discovery procedure.

PMID: 26415842 [PubMed - indexed for MEDLINE]

Complete haplotype phasing of the MHC and KIR loci with targeted HaploSeq.

BMC Genomics. 2015;16:900

Authors: Selvaraj S, Schmitt AD, Dixon JR, Ren B

Abstract
BACKGROUND: The MHC and KIR loci are clinically relevant regions of the genome. Typing the sequence of these loci has a wide range of applications including organ transplantation, drug discovery, pharmacogenomics and furthering fundamental research in immune genetics. Rapid advances in biochemical and next-generation sequencing (NGS) technologies have enabled several strategies for precise genotyping and phasing of candidate HLA alleles. Nonetheless, as typing of candidate HLA alleles alone reveals limited aspects of the genetics of MHC region, it is insufficient for the comprehensive utility of the aforementioned applications. For this reason, we believe phasing the entire MHC and KIR locus onto a single locus-spanning haplotype can be a critical improvement for better understanding transplantation biology.
RESULTS: Generating long-range (>1 Mb) phase information is traditionally very challenging. As proximity-ligation based methods of DNA sequencing preserves chromosome-span phase information, we have utilized this principle to demonstrate its utility towards generating full-length phasing of MHC and KIR loci in human samples. We accurately (~99%) reconstruct the complete haplotypes for over 90% of sequence variants (coding and non-coding) within these two loci that collectively span 4-megabases.
CONCLUSIONS: By haplotyping a majority of coding and non-coding alleles at the MHC and KIR loci in a single assay, this method has the potential to assist transplantation matching and facilitate investigation of the genetic basis of human immunity and disease.

PMID: 26541200 [PubMed - indexed for MEDLINE]

Pharmacogenetics of BCR/ABL Inhibitors in Chronic Myeloid Leukemia.

Int J Mol Sci. 2015;16(9):22811-29

Authors: Polillo M, Galimberti S, Baratè C, Petrini M, Danesi R, Di Paolo A

Abstract
Chronic myeloid leukemia was the first haematological neoplasia that benefited from a targeted therapy with imatinib nearly 15 years ago. Since then, several studies have investigated the role of genes, their variants (i.e., polymorphisms) and their encoded proteins in the pharmacokinetics and pharmacodynamics of BCR-ABL1 tyrosine kinase activity inhibitors (TKIs). Transmembrane transporters seem to influence in a significant manner the disposition of TKIs, especially that of imatinib at both cellular and systemic levels. In particular, members of the ATP-binding cassette (ABC) family (namely ABCB1 and ABCG2) together with solute carrier (SLC) transporters (i.e., SLC22A1) are responsible for the differences in drug pharmacokinetics. In the case of the newer TKIs, such as nilotinib and dasatinib, the substrate affinity of these drugs for transporters is variable but lower than that measured for imatinib. In this scenario, the investigation of genetic variants as possible predictive markers has led to some discordant results. With the partial exception of imatinib, these discrepancies seem to limit the application of discovered biomarkers in the clinical settings. In order to overcome these issues, larger prospective confirmative trials are needed.

PMID: 26402671 [PubMed - indexed for MEDLINE]

Report on the Workshop and Regular Meeting of the Imode-CKD and Bcmolmed Marie Curie Training and Research Programs.

Pril (Makedon Akad Nauk Umet Odd Med Nauki). 2015 Dec 1;36(2):235-240

Authors: Krochmal M, Cisek K, Markoska K, Spasovski G, Vlahou A

Abstract
A Workshop and Regular Meeting of the Marie Curie Training and Research Programs iMODECKD (Identification of the Molecular Determinants of established Chronic Kidney Disease) and BCMolMed (Molecular Medicine for Bladder Cancer) was held from 20-22 March at the Macedonian Academy of Science and Arts (MASA). The meeting was hosted by the participating center University of Skopje (SKO) - Goce Spasovski and MASA - Momir Polenakovic (R. Macedonia). The representative from MASA proteomic research center - Katerina Davalieva (R. Macedonia) had presentation on proteomic research in prostate cancer (PCa). 40 researchers from 13 different countries participated at the meeting. The Workshop was devoted on "Chronic Kidney Disease: Clinical Management issues", and consisted of 15 oral presentations given by nephrologists and experts in the field of CKD. Raymond Vanholder (Belgium) - past president of ERA-EDTA had a keynote lecture on "CKD: Questions that need to be answered and are not (or at least not entirely)". The workshop continued in four sessions with lectures from Alberto Ortiz (Spain), Olivera Stojceva-Taneva (R. Macedonia), Dimitrios Goumenos (Greece), Joachim Beige (Germany), Marian Klinger (Poland), Goce Spasovski (R. Macedonia), Joachim Jankowski (Germany), Adalbert Schiller (Romania), Robert Johnson (USA), Franco Ferrario (Italy), Ivan Rychlik (Czech Republic), Fulvio Magni (Italy) and Giovambattista Capasso (Italy), all covering a training theme. Within the meeting there were two lectures on complimentary skills for ethics in science and career advancement from two principal investigators - Goce Spasovski (R. Macedonia) and Joost Schanstra (France). During the Regular Meeting, 13 PhD students i.e. Early Stage Researchers and one Experienced Researcher from both Programs presented their work and progress within iMODE-CKD and BCMolMed projects. This meeting was a great opportunity to exchange experience and ideas in the field of systems biology approaches and translational medicine and planning future collaboration.

PMID: 27442390 [PubMed - as supplied by publisher]

Novel molecular triggers underlie valproate-induced liver injury and its alleviation by the omega-3 fatty acid DHA: role of inflammation and apoptosis.

Heliyon. 2016 Jul;2(7):e00130

Authors: El-Mowafy AM, Katary MM, Pye C, Ibrahim AS, Elmarakby AA

Abstract
BACKGROUND/AIM: Hepatic injury is a hallmark adverse reaction to Valproate (VPA), a common used drug in the management of numerous CNS disorders, including epilepsy. DHA has a myriad of health benefits, including renal- and hepato-protective effects. Unfortunately, however, the underpinnings of such liver-pertinent VPA- and DHA-actions remain largely undefined. Accordingly, this study attempted to unveil the cellular and molecular triggers whereby VPA evokes, while DHA abates, hepatotoxicity.
METHODS: We evaluated activity and/or expression of cellular markers of oxidative stress, inflammation, and apoptosis in rat liver, following treatment with VPA (500 mg/kg/day) with and without concurrent treatment with DHA (250 mg/kg/day) for two weeks.
RESULTS AND CONCLUSION: VPA promoted hepatic oxidative stress as evidenced by enhancing activity/expression of NADPH-oxidase and its subunits, a ROS-generator, and by accumulation of lipid-peroxides. Moreover, VPA enhanced hepatic phosphorylation/activation of mitogen-activated protein kinase (MAPK), and expression of cyclooxygenase-2(COX-2), as proinflammatory signals. Besides, VPA promoted hepatocellular apoptosis, as attested by enhanced expression of cleaved caspase-9 and increased number of TUNEL-positive hepatocytes. Lastly, VPA upregulated levels of hypoxia-inducible factor-1-alpha (HIF-1α), a multifaceted modulator of hepatocytic biology, and activity of its downstream antioxidant enzyme heme-oxygenase-1(HO-1). These changes were significantly blunted by co-administration of DHA. Our findings demonstrate that VPA activated NADPH-oxidase and HIF-1α to induce oxidative-stress and hypoxia as initiators of hepatic injury. These changes were further aggravated by up-regulation of inflammatory (MAPK and COX-2) and apoptotic cascades, but could be partly lessened by HO-1 activation. Concurrent administration of DHA mitigated all VPA-induced anomalies.

PMID: 27441301 [PubMed]

Noise processing by microRNA-mediated circuits: The Incoherent Feed-Forward Loop, revisited.

Heliyon. 2016 Apr;2(4):e00095

Authors: Grigolon S, Di Patti F, De Martino A, Marinari E

Abstract
The intrinsic stochasticity of gene expression is usually mitigated in higher eukaryotes by post-transcriptional regulation channels that stabilise the output layer, most notably protein levels. The discovery of small non-coding RNAs (miRNAs) in specific motifs of the genetic regulatory network has led to identifying noise buffering as the possible key function they exert in regulation. Recent in vitro and in silico studies have corroborated this hypothesis. It is however also known that miRNA-mediated noise reduction is hampered by transcriptional bursting in simple topologies. Here, using stochastic simulations validated by analytical calculations based on van Kampen's expansion, we revisit the noise-buffering capacity of the miRNA-mediated Incoherent Feed Forward Loop (IFFL), a small module that is widespread in the gene regulatory networks of higher eukaryotes, in order to account for the effects of intermittency in the transcriptional activity of the modulator gene. We show that bursting considerably alters the circuit's ability to control static protein noise. By comparing with other regulatory architectures, we find that direct transcriptional regulation significantly outperforms the IFFL in a broad range of kinetic parameters. This suggests that, under pulsatile inputs, static noise reduction may be less important than dynamical aspects of noise and information processing in characterising the performance of regulatory elements.

PMID: 27441269 [PubMed]

Hydrogen peroxide induced cell death: One or two modes of action?

Heliyon. 2015 Dec;1(4):e00049

Authors: Uhl L, Gerstel A, Chabalier M, Dukan S

Abstract
Imlay and Linn show that exposure of logarithmically growing Escherichia coli to hydrogen peroxide (H2O2) leads to two kinetically distinguishable modes of cell killing. Mode one killing is pronounced near 1 mM concentration of H2O2 and is caused by DNA damage, whereas mode-two killing requires higher concentration ([Formula: see text]). The second mode seems to be essentially due to damage to all macromolecules. This phenomenon has also been observed in Fenton in vitro systems with DNA nicking caused by hydroxyl radical ([Formula: see text]). To our knowledge, there is currently no mathematical model for predicting mode one killing in vitro or in vivo after H2O2 exposure. We propose a simple model, using Escherichia coli as a model organism and a set of ordinary differential equations. Using this model, we show that available iron and cell density, two factors potentially involved in ROS dynamics, play a major role in the prediction of the experimental results obtained by our team and in previous studies. Indeed the presence of the mode one killing is strongly related to those two parameters. To our knowledge, mode-one death has not previously been explained. Imlay and Linn (Imlay and Linn, 1986) suggested that perhaps the amount of the toxic species was reduced at high concentrations of H2O2 because hydroxyl (or other) radicals might be quenched directly by hydrogen peroxide with the concomitant formation of superoxide anion (a less toxic species). We demonstrate (mathematically and numerically) that free available iron decrease is necessary to explain mode one killing which cannot appear without it and that H2O2 quenching or consumption is not responsible for mode-one death. We are able to follow ROS concentration (particularly responsible for mode one killing) after exposure to H2O2. This model therefore allows us to understand two major parameters involved in the presence or not of the first killing mode.

PMID: 27441232 [PubMed]

Construction and Evaluation of an Organic Anion Transporter 1 (OAT1)-Centered Metabolic Network.

J Biol Chem. 2016 Jul 20;

Authors: Liu HC, Jamshidi N, Chen Y, Eraly SA, Cho SY, Bhatnagar V, Wu W, Bush KT, Abagyan R, Palsson BO, Nigam SK

Abstract
There has been a recent interest in the broader physiological importance of multispecific drug transporters of the SLC and ABC transporter families. Here, a novel multi-tiered systems biology approach was used to predict metabolites and signaling molecules potentially affected by the in vivo deletion of organic anion transporter 1 (Oat1, Slc22a6, originally NKT), a major kidney-expressed drug transporter. Validation of some predictions in wet-lab assays, together with re-evaluation of existing transport and knockout metabolomics data, generated an experimentally-validated, confidence-ranked set of OAT1-interacting endogenous compounds enabling construction of an OAT1-centered metabolic interaction network. Pathway and enrichment analysis indicated an important role for OAT1 in metabolism involving: the TCA cycle, tryptophan and other amino acids, fatty acids, prostaglandins, cyclic nucleotides, odorants, polyamines, and vitamins. The partly-validated reconstructed network is also consistent with a major role for OAT1 in modulating metabolic and signaling pathways involving uric acid, gut microbiome products and so-called uremic toxins accumulating in chronic kidney disease (CKD). Together, the findings are compatible with the hypothesized role of drug transporters in remote inter-organ and inter-organismal communication (the Remote Sensing and Signaling Hypothesis, Nigam SK. 2015, Nature Rev Drug Disc 14:29). The fact that OAT1 can affect many systemic biological pathways suggests that drug-metabolite interactions (DMI) need to be considered beyond simple competition for the drug transporter itself and may explain aspects of drug-induced metabolic syndromes. Our approach should provide novel mechanistic insights into the role of OAT1 and other drug transporters implicated in metabolic diseases like gout, diabetes and CKD.

PMID: 27440044 [PubMed - as supplied by publisher]

Mission Critical: The Need for Proteomics in the Era of Next-Generation Sequencing and Precision Medicine.

Hum Mol Genet. 2016 Jul 20;

Authors: Cayer D, Nazor KL, Schork NJ

Abstract
Next generation sequencing (NGS) has ignited an unprecedented pace of discovery in the biomedical sciences that is fundamentally transforming the way that we understand, diagnose and treat disease, and has motivated the belief that true precision medicine - medicine that is tailored to an individual's genetic, biochemical and exposure profile - will be a reality in the near term. With minimal sample requirement, NGS can enable the concurrent genome-wide study of genetic variations, transcriptomes, and certain epigenetic modifications. However, interrogating proteins in as efficiently as DNA and RNA can be interrogated with NGS is lacking and this hampers more comprehensive views of molecular physiology and limits advances in biomedical science and precision medicine. The fact is that innovations in proteomic technologies pale in comparison to advances in NGS, with current methodologies suffering from issues related to reproducibility, sensitivity, sample requirements, and limited multiplexing capacity. The development of proteomic technologies to overcome these limitations would fill the void in systems biology research, catalyze clinical innovations, and expedite the realization of precision medicine.

PMID: 27439388 [PubMed - as supplied by publisher]

Simulation technology and its application in Systems Biology.

Nihon Yakurigaku Zasshi. 2016 Feb;147(2):101-6

Authors: Funahashi A, Hiroi N

PMID: 26860650 [PubMed - indexed for MEDLINE]

CauloBrowser: A systems biology resource for Caulobacter crescentus.

Nucleic Acids Res. 2016 Jan 4;44(D1):D640-5

Authors: Lasker K, Schrader JM, Men Y, Marshik T, Dill DL, McAdams HH, Shapiro L

Abstract
Caulobacter crescentus is a premier model organism for studying the molecular basis of cellular asymmetry. The Caulobacter community has generated a wealth of high-throughput spatiotemporal databases including data from gene expression profiling experiments (microarrays, RNA-seq, ChIP-seq, ribosome profiling, LC-ms proteomics), gene essentiality studies (Tn-seq), genome wide protein localization studies, and global chromosome methylation analyses (SMRT sequencing). A major challenge involves the integration of these diverse data sets into one comprehensive community resource. To address this need, we have generated CauloBrowser (www.caulobrowser.org), an online resource for Caulobacter studies. This site provides a user-friendly interface for quickly searching genes of interest and downloading genome-wide results. Search results about individual genes are displayed as tables, graphs of time resolved expression profiles, and schematics of protein localization throughout the cell cycle. In addition, the site provides a genome viewer that enables customizable visualization of all published high-throughput genomic data. The depth and diversity of data sets collected by the Caulobacter community makes CauloBrowser a unique and valuable systems biology resource.

PMID: 26476443 [PubMed - indexed for MEDLINE]

Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Sep-Oct;12(5):1008-20

Authors: Misra S, Pamnany K, Aluru S

Abstract
Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

PMID: 26451815 [PubMed - indexed for MEDLINE]

Expert-Guided Generative Topographical Modeling with Visual to Parametric Interaction.

PLoS One. 2016;11(2):e0129122

Authors: Han C, House L, Leman SC

Abstract
Introduced by Bishop et al. in 1996, Generative Topographic Mapping (GTM) is a powerful nonlinear latent variable modeling approach for visualizing high-dimensional data. It has shown useful when typical linear methods fail. However, GTM still suffers from drawbacks. Its complex parameterization of data make GTM hard to fit and sensitive to slight changes in the model. For this reason, we extend GTM to a visual analytics framework so that users may guide the parameterization and assess the data from multiple GTM perspectives. Specifically, we develop the theory and methods for Visual to Parametric Interaction (V2PI) with data using GTM visualizations. The result is a dynamic version of GTM that fosters data exploration. We refer to the new version as V2PI-GTM. In this paper, we develop V2PI-GTM in stages and demonstrate its benefits within the context of a text mining case study.

PMID: 26905728 [PubMed - indexed for MEDLINE]

DESM: portal for microbial knowledge exploration systems.

Nucleic Acids Res. 2016 Jan 4;44(D1):D624-33

Authors: Salhi A, Essack M, Radovanovic A, Marchand B, Bougouffa S, Antunes A, Simoes MF, Lafi FF, Motwalli OA, Bokhari A, Malas T, Amoudi SA, Othum G, Allam I, Mineta K, Gao X, Hoehndorf R, C Archer JA, Gojobori T, Bajic VB

Abstract
Microorganisms produce an enormous variety of chemical compounds. It is of general interest for microbiology and biotechnology researchers to have means to explore information about molecular and genetic basis of functioning of different microorganisms and their ability for bioproduction. To enable such exploration, we compiled 45 topic-specific knowledgebases (KBs) accessible through DESM portal (www.cbrc.kaust.edu.sa/desm). The KBs contain information derived through text-mining of PubMed information and complemented by information data-mined from various other resources (e.g. ChEBI, Entrez Gene, GO, KOBAS, KEGG, UniPathways, BioGrid). All PubMed records were indexed using 4,538,278 concepts from 29 dictionaries, with 1 638 986 records utilized in KBs. Concepts used are normalized whenever possible. Most of the KBs focus on a particular type of microbial activity, such as production of biocatalysts or nutraceuticals. Others are focused on specific categories of microorganisms, e.g. streptomyces or cyanobacteria. KBs are all structured in a uniform manner and have a standardized user interface. Information exploration is enabled through various searches. Users can explore statistically most significant concepts or pairs of concepts, generate hypotheses, create interactive networks of associated concepts and export results. We believe DESM will be a useful complement to the existing resources to benefit microbiology and biotechnology research.

PMID: 26546514 [PubMed - indexed for MEDLINE]

24 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/21

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.