| Nome |
# |
|
Network-based approaches to explore complex biological systems towards network medicine, file e383531c-5ff3-15e8-e053-a505fe0a3de9
|
284
|
|
Network analysis of gut microbiome and metabolome to discover microbiota-linked biomarkers in patients affected by non-small cell lung cancer, file e3835328-e818-15e8-e053-a505fe0a3de9
|
177
|
|
JARID1B expression and its function in DNA damage repair are tightly regulated by miRNAs in breast cancer, file e3835321-fc70-15e8-e053-a505fe0a3de9
|
161
|
|
A new procedure to analyze RNA non-branching structures, file e3835321-db12-15e8-e053-a505fe0a3de9
|
151
|
|
PVT1: a rising star among oncogenic long non-coding RNAs, file e3835312-3769-15e8-e053-a505fe0a3de9
|
123
|
|
Polaronic and nonadiabatic phase diagram from anomalous isotope effects, file e3835325-57ab-15e8-e053-a505fe0a3de9
|
123
|
|
Phylogenetic and metabolic tracking of gut microbiota during perinatal development., file e3835314-ac3b-15e8-e053-a505fe0a3de9
|
122
|
|
Nonadiabatic high-Tc superconductivity in hole-doped fullerenes, file e3835325-4306-15e8-e053-a505fe0a3de9
|
122
|
|
A simplified genomic profiling approach predicts outcome in metastatic colorectal cancer, file e383531f-2297-15e8-e053-a505fe0a3de9
|
121
|
|
Convolutional neural networks for automated classification of prostate multiparametric magnetic resonance imaging based on image quality, file e383532c-cf0d-15e8-e053-a505fe0a3de9
|
120
|
|
Gut microbiota signatures in cystic fibrosis. Loss of host CFTR function drives the microbiota enterophenotype, file e3835322-19b2-15e8-e053-a505fe0a3de9
|
117
|
|
Role of the long non-coding RNA PVT1 in the dysregulation of the ceRNA-ceRNA network in human breast cancer, file e3835316-a285-15e8-e053-a505fe0a3de9
|
111
|
|
MIENTURNET: An interactive web tool for microRNA-target enrichment and network-based analysis, file e3835323-d907-15e8-e053-a505fe0a3de9
|
109
|
|
SWIM tool application to expression data of glioblastoma stem-like cell lines, corresponding primary tumors and conventional glioma cell lines, file e3835325-192f-15e8-e053-a505fe0a3de9
|
109
|
|
Integrated transcriptomic correlation network analysis identifies COPD molecular determinants, file e3835324-e973-15e8-e053-a505fe0a3de9
|
108
|
|
Relevance of multiband Jahn-Teller effects on the electron-phonon interaction in A3C60, file e3835325-312f-15e8-e053-a505fe0a3de9
|
106
|
|
Computational identification of specific genes for glioblastoma stem-like cells identity, file e3835321-d55d-15e8-e053-a505fe0a3de9
|
102
|
|
SWIM: A computational tool to unveiling crucial nodes in complex biological networks, file e3835316-b8cc-15e8-e053-a505fe0a3de9
|
97
|
|
Network analysis integrating microRNA expression profiling with MRI biomarkers and clinical data for prostate cancer early detection: a proof of concept study, file e383532d-5ef2-15e8-e053-a505fe0a3de9
|
96
|
|
An integrative in-silico analysis discloses a novel molecular subset of colorectal cancer possibly eligible for immune checkpoint immunotherapy, file e383532f-15b0-15e8-e053-a505fe0a3de9
|
90
|
|
The oncogenic role of circPVT1 in head and neck squamous cell carcinoma is mediated through the mutant p53/YAP/TEAD transcription-competent complex, file e3835318-da56-15e8-e053-a505fe0a3de9
|
88
|
|
SAveRUNNER: A network-based algorithm for drug repurposing and its application to COVID-19, file e383532a-a0c3-15e8-e053-a505fe0a3de9
|
84
|
|
A perspective on the algorithms predicting and evaluating the RNA secondary structure, file e3835324-d98a-15e8-e053-a505fe0a3de9
|
75
|
|
Stochastic Modeling of Expression Kinetics Identifies Messenger Half-Lives and Reveals Sequential Waves of Co-ordinated Transcription and Decay, file e3835311-e401-15e8-e053-a505fe0a3de9
|
73
|
|
Distinct transcriptome responses to water limitation in isohydric and anisohydric grapevine cultivars, file e3835324-d987-15e8-e053-a505fe0a3de9
|
66
|
|
GIANT: A Cytoscape Plugin for Modular Networks, file e3835325-1939-15e8-e053-a505fe0a3de9
|
66
|
|
Polymorphonuclear Myeloid-Derived Suppressor Cells Are Abundant in Peripheral Blood of Cancer Patients and Suppress Natural Killer Cell Anti-Tumor Activity, file e383532e-374c-15e8-e053-a505fe0a3de9
|
66
|
|
Computational analysis identifies a sponge interaction network between long non-coding RNAs and messenger RNAs in human breast cancer, file e3835325-512d-15e8-e053-a505fe0a3de9
|
65
|
|
The new paradigm of Network Medicine to analyse breast cancer phenotypes, file e3835328-2c0b-15e8-e053-a505fe0a3de9
|
65
|
|
SEaCorAl: Identifying and contrasting the regulation-correlation bias in RNA-Seq paired expression data of patient groups, file e383532c-6e8a-15e8-e053-a505fe0a3de9
|
65
|
|
miR-96-5p targets PTEN expression affecting radio-chemosensitivity of HNSCC cells, file e3835325-108c-15e8-e053-a505fe0a3de9
|
64
|
|
Prediction of response to vemurafenib in BRAF V600E mutant cancers based on a network approach, file e3835325-691d-15e8-e053-a505fe0a3de9
|
64
|
|
Prostate cancer screening research can benefit from network medicine: an emerging awareness, file e3835325-da15-15e8-e053-a505fe0a3de9
|
62
|
|
Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer, file e3835325-9978-15e8-e053-a505fe0a3de9
|
61
|
|
Gene co-expression in the interactome: moving from correlation toward causation via an integrated approach to disease module discovery, file e3835329-af57-15e8-e053-a505fe0a3de9
|
60
|
|
Ultrasensitive HCV RNA quantification in antiviral triple therapy: new insight on viral clearance dynamics and treatment outcome predictors, file e3835325-1937-15e8-e053-a505fe0a3de9
|
56
|
|
In silico drug repurposing in COVID-19. A network-based analysis, file e383532d-0256-15e8-e053-a505fe0a3de9
|
55
|
|
Human Papillomavirus infections in cervical samples from HIV-positive women: evaluation of the presence of the nonavalent HPV genotypes and genetic diversity, file e3835328-fe82-15e8-e053-a505fe0a3de9
|
53
|
|
Polymorphonuclear myeloid-derived suppressor cells impair the anti-tumor efficacy of gd2.car t-cells in patients with neuroblastoma, file e383532d-5c87-15e8-e053-a505fe0a3de9
|
52
|
|
Clinical epigenetics settings for cancer and cardiovascular diseases: real-life applications of network medicine at the bedside, file e383532b-ef8d-15e8-e053-a505fe0a3de9
|
45
|
|
SAveRUNNER: an R-based tool for drug repurposing, file e383532b-f673-15e8-e053-a505fe0a3de9
|
44
|
|
The role of FOSL1 in stem-like cell reprogramming processes, file e383532d-1019-15e8-e053-a505fe0a3de9
|
38
|
|
A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases, file e383532e-9bbc-15e8-e053-a505fe0a3de9
|
36
|
|
In silico recognition of a prognostic signature in basal-like breast cancer patients, file e383532d-f3d3-15e8-e053-a505fe0a3de9
|
24
|
|
Assessing the impact of data-driven limitations on tracing and forecasting the outbreak dynamics of COVID-19, file e383532c-ccf0-15e8-e053-a505fe0a3de9
|
22
|
|
Drug Repurposing: A Network-based Approach to Amyotrophic Lateral Sclerosis, file e383532c-cf10-15e8-e053-a505fe0a3de9
|
22
|
|
GZMKhigh CD8+ T effector memory cells are associated with CD15high neutrophil abundance in non-metastatic colorectal tumors and predict poor clinical outcome, file 819ea30d-753a-49b5-bd75-7330bfff4ab0
|
18
|
|
Integro-differential approach for modeling the COVID-19 dynamics - Impact of confinement measures in Italy, file e383532d-59fd-15e8-e053-a505fe0a3de9
|
18
|
|
Transcriptomics and metabolomics integration reveals redox-dependent metabolic rewiring in breast cancer cells, file e383532d-5c89-15e8-e053-a505fe0a3de9
|
17
|
|
Comprehensive network medicine-based drug repositioning via integration of therapeutic efficacy and side effects, file e383532e-af33-15e8-e053-a505fe0a3de9
|
15
|
|
Disruption of redox homeostasis for combinatorial drug eefficacy in K-Ras tumors as revealed by metabolic connectivity proling, file e383532c-b007-15e8-e053-a505fe0a3de9
|
13
|
|
StaRTrEK:in silico estimation of RNA half-lives from genome-wide time-course experiments without transcriptional inhibition, file e383532f-4239-15e8-e053-a505fe0a3de9
|
13
|
|
A Network of MicroRNAs and mRNAs Involved in Melanosome Maturation and Trafficking Defines the Lower Response of Pigmentable Melanoma Cells to Targeted Therapy, file 7ca43586-2bea-401f-ab7a-9b1b399e7d3c
|
12
|
|
Integrated network analysis for studying human lung squamous cell carcinoma, file e3835325-0ed7-15e8-e053-a505fe0a3de9
|
10
|
|
Prospective validation study of a novel integrated pathway based on clinical features, MRI biomarkers and microRNAs for early detection of prostate cancer, file 0224210e-fe5d-4111-a701-b5457a256d24
|
8
|
|
SPINNAKER: an R-based tool to highlight key RNA interactions in complex biological networks, file e383532f-02b5-15e8-e053-a505fe0a3de9
|
7
|
|
Repurposing Histaminergic Drugs in Multiple Sclerosis, file 370d2a0b-701a-497a-8751-83b6534b3eac
|
6
|
|
Alzheimer’s disease: insights from a network medicine perspective, file 9ca972b1-6f53-4c3d-b8e8-fef095e8915a
|
4
|
|
BRAF V600E -mutant cancers display a variety of networks by SWIM analysis: prediction of vemurafenib clinical response, file e3835321-ef52-15e8-e053-a505fe0a3de9
|
4
|
|
Gut microbiota profiling of pediatric nonalcoholic fatty liver disease and obese patients unveiled by an integrated meta-omics-based approach, file e3835317-047e-15e8-e053-a505fe0a3de9
|
3
|
|
Gut Microbiota Ecology and Inferred Functions in Children With ASD Compared to Neurotypical Subjects, file af15dc6f-5674-4a2e-a055-13cb11b5f406
|
2
|
|
Kinetic effects and modeling of mRNA turnover, file e383531b-80af-15e8-e053-a505fe0a3de9
|
2
|
|
Identification of Disease-miRNA networks across different cancer types using SWIM, file e3835320-b9f8-15e8-e053-a505fe0a3de9
|
2
|
|
Network Inference and Reconstruction in Bioinformatics, file e3835320-d1c1-15e8-e053-a505fe0a3de9
|
2
|
|
A paradigm shift in medicine: a comprehensive review of network-based approaches, file e3835323-beda-15e8-e053-a505fe0a3de9
|
2
|
|
Interplay between long non-coding RNAs and microRNAs in cancer, file e3835324-d985-15e8-e053-a505fe0a3de9
|
2
|
|
Modules Identification in Protein Structures: The Topological and Geometrical Solutions, file e3835325-1089-15e8-e053-a505fe0a3de9
|
2
|
|
Molecular networks in Network Medicine: Development and applications, file e3835325-e9d1-15e8-e053-a505fe0a3de9
|
2
|
|
Mining sponge phenomena in RNA expression data, file e383532e-3d9b-15e8-e053-a505fe0a3de9
|
2
|
|
A gene dosage‐dependent effect unveils NBS1 as both a haploinsufficient tumour suppressor and an essential gene for SHH‐medulloblastoma, file 5ba8a075-03d8-4c4c-b348-2b228fc87a15
|
1
|
|
Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development, file e3835312-3768-15e8-e053-a505fe0a3de9
|
1
|
|
A feature-based integrated scoring scheme for cell cycle-regulated genes prioritization, file e383531c-8ace-15e8-e053-a505fe0a3de9
|
1
|
|
The clinical significance of HCV core antigen detection during Telaprevir/Peg-Interferon/Ribavirin therapy in patients with HCV 1 genotype infection, file e3835325-0ed9-15e8-e053-a505fe0a3de9
|
1
|
|
Inverse Problems in Systems Biology: A Critical Review, file e3835325-0eda-15e8-e053-a505fe0a3de9
|
1
|
|
Are proteins just coiled cords? Local and Global analysis of Contact Maps reveals the backbone-dependent nature of proteins, file e3835325-108a-15e8-e053-a505fe0a3de9
|
1
|
|
Identifying Correlations between Chromosomal Proximity of Genes and Distance of Their Products in Protein-Protein Interaction Networks of Yeast, file e3835325-1932-15e8-e053-a505fe0a3de9
|
1
|
|
Ripening Transcriptomic Program in Red and White Grapevine Varieties Corre- lates with Berry Skin Anthocyanin Accumulation, file e3835325-1933-15e8-e053-a505fe0a3de9
|
1
|
|
Mutant p53 inhibits miRNA biogenesis by interfering with the Microprocessor complex, file e3835325-1934-15e8-e053-a505fe0a3de9
|
1
|
|
Genetic, epigenetic and genomic effects on variation of gene expression among grape varieties, file e3835325-193a-15e8-e053-a505fe0a3de9
|
1
|
|
On the integration of protein-protein interaction networks with gene expression and 3D structural data: What can be gained?, file e3835325-697b-15e8-e053-a505fe0a3de9
|
1
|
|
Gene network analysis using SWIM reveals interplay between the transcription factor-encoding genes HMGA1, FOXM1, and MYBL2 in triple-negative breast cancer, file e383532c-d9c3-15e8-e053-a505fe0a3de9
|
1
|
|
An Overview of the computational models dealing with the regulatory ceRNA mechanism and ceRNA deregulation in cancer, file e383532d-03f3-15e8-e053-a505fe0a3de9
|
1
|
| Totale |
4.199 |