01577nas a2200253   4500008004100000022001400041245005600055210005300111260001600164300000600180490000700186520083300193100001601026700002701042700002201069700001801091700002101109700002001130700001901150700002301169700002401192700002001216856008701236       2021                        eng d  a1756-038100aMechanistic modeling of the SARS-CoV-2 disease map.0 aMechanistic modeling of the SARSCoV2 disease map  c2021 Jan 21  a50 v143 a<p>Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.</p>1 aRian, Kinza1 aEsteban-Medina, Marina1 aHidalgo, Marta, R1 aCubuk, Cankut1 aFalco, Matias, M1 aLoucera, Carlos1 aGunyel, Devrim1 aOstaszewski, Marek1 aPeña-Chilet, Maria1 aDopazo, Joaquin  uhttps://www.clinbioinfosspa.es/content/mechanistic-modeling-sars-cov-2-disease-map01087nas a2200313   4500008004100000022001400041245014500055210006900200260001500269300000800284490000600292653002800298653001300326653002300339653001100362653002100373653003300394653003100427653001300458653001500471653002400486100002000510700002700530700001600557700002100573700002000594700002400614856013500638       2020                        eng d  a2059-363500aDrug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection.0 aDrug repurposing for COVID19 using machine learning and mechanis  c2020 12 11  a2900 v510aComputational Chemistry10aCOVID-1910adrug repositioning10aHumans10aMachine Learning10aMolecular Docking Simulation10aMolecular Targeted Therapy10aProteins10aSARS-CoV-210aSignal Transduction1 aLoucera, Carlos1 aEsteban-Medina, Marina1 aRian, Kinza1 aFalco, Matias, M1 aDopazo, Joaquin1 aPeña-Chilet, Maria  uhttps://www.clinbioinfosspa.es/content/drug-repurposing-covid-19-using-machine-learning-and-mechanistic-models-signal-transduction00750nas a2200157   4500008004100000245011500041210006900156260001600225490000600241100002100247700002400268700002000292700002200312700002000334856023800354       2020                        eng d00aMechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscapeAbstract0 aMechanistic models of signaling pathways deconvolute the gliobla  cJan-06-20200 v21 aFalco, Matias, M1 aPeña-Chilet, Maria1 aLoucera, Carlos1 aHidalgo, Marta, R1 aDopazo, Joaquin  uhttps://academic.oup.com/narcancer/article/doi/10.1093/narcan/zcaa011/5862620http://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdfhttp://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdf02758nas a2200373   4500008004100000022001400041245009300055210006900148260001500217300001400232490000700246520158800253653002801841653001101869653003501880653002401915653001801939653001301957653001701970653001801987653002202005100001702027700002102044700002102065700002002086700002902106700002002135700002202155700002002177700001902197700001702216700002302233856012802256       2020                        eng d  a1549-491800aPlatform to study intracellular polystyrene nanoplastic pollution and clinical outcomes.0 aPlatform to study intracellular polystyrene nanoplastic pollutio  c2020 10 01  a1321-13250 v383 a<p>Increased pollution by plastics has become a serious global environmental problem, but the concerns for human health have been raised after reported presence of microplastics (MPs) and nanoplastics (NPs) in food and beverages. Unfortunately, few studies have investigate the potentially harmful effects of MPs/NPs on early human development and human health. Therefore, we used a new platform to study possible effects of polystyrene NPs (PSNPs) on the transcription profile of preimplantation human embryos and human induced pluripotent stem cells (hiPSCs). Two pluripotency genes, LEFTY1 and LEFTY2, which encode secreted ligands of the transforming growth factor-beta, were downregulated, while CA4 and OCLM, which are related to eye development, were upregulated in both samples. The gene set enrichment analysis showed that the development of atrioventricular heart valves and the dysfunction of cellular components, including extracellular matrix, were significantly affected after exposure of hiPSCs to PSNPs. Finally, using the HiPathia method, which uncovers disease mechanisms and predicts clinical outcomes, we determined the APOC3 circuit, which is responsible for increased risk for ischemic cardiovascular disease. These results clearly demonstrate that better understanding of NPs bioactivities and its implications for human health is of extreme importance. Thus, the presented platform opens further aspects to study interactions between different environmental and intracellular pollutions with the aim to decipher the mechanism and origin of human diseases.</p>10aEnvironmental Pollution10aHumans10aInduced Pluripotent Stem Cells10aIntracellular Space10aNanoparticles10aPlastics10aPolystyrenes10aTranscriptome10aTreatment Outcome1 aBojic, Sanja1 aFalco, Matias, M1 aStojkovic, Petra1 aLjujic, Biljana1 aJankovic, Marina, Gazdic1 aArmstrong, Lyle1 aMarkovic, Nebojsa1 aDopazo, Joaquin1 aLako, Majlinda1 aBauer, Roman1 aStojkovic, Miodrag  uhttps://www.clinbioinfosspa.es/content/platform-study-intracellular-polystyrene-nanoplastic-pollution-and-clinical-outcomes01876nas a2200181   4500008004100000022001400041245005400055210004800109260001600157300001000173490000600183520137000189100002101559700001701580700003101597700002101628856004501649       2016                        eng d  a2045-232200aThe pan-cancer pathological regulatory landscape.0 apancancer pathological regulatory landscape  c2016 Dec 21  a397090 v63 aDysregulation of the normal gene expression program is the cause of a broad range of diseases, including cancer. Detecting the specific perturbed regulators that have an effect on the generation and the development of the disease is crucial for understanding the disease mechanism and for taking decisions on efficient preventive and curative therapies. Moreover, detecting such perturbations at the patient level is even more important from the perspective of personalized medicine. We applied the Transcription Factor Target Enrichment Analysis, a method that detects the activity of transcription factors based on the quantification of the collective transcriptional activation of their targets, to a large collection of 5607 cancer samples covering eleven cancer types. We produced for the first time a comprehensive catalogue of altered transcription factor activities in cancer, a considerable number of them significantly associated to patient’s survival. Moreover, we described several interesting TFs whose activity do not change substantially in the cancer with respect to the normal tissue but ultimately play an important role in patient prognostic determination, which suggest they might be promising therapeutic targets. An additional advantage of this method is that it allows obtaining personalized TF activity estimations for individual patients.1 aFalco, Matias, M1 aBleda, Marta1 aCarbonell-Caballero, José1 aDopazo, Joaquín  uhttp://www.nature.com/articles/srep39709