31 to 40 of 348 Results
Feb 22, 2024 - Replication Data for Changes of RAS pathway phosphorylation in lymphoblastoid cell lines from Noonan syndrome patients carrying hypomorphic variants in two NS genes
Capitanio, Daniele, 2022, "Replication Data for Changes of RAS pathway phosphorylation in lymphoblastoid cell lines from Noonan syndrome patients carrying hypomorphic variants in two NS genes", https://doi.org/10.13130/RD_UNIMI/PKZ7FJ, UNIMI Dataverse, V2, UNF:6:dpRfYCpzZVtAKNFc5ju7FQ== [fileUNF]
This dataset include the LC-MS/MS proteomics and phosphoproteomics datasets of changed proteins generated in the study: "Changes of RAS pathway phosphorylation in lymphoblastoid cell lines from Noonan syndrome patients carrying hypomorphic variants in two NS genes" by Viviana Tri... |
Feb 22, 2024 - Replication Data for Proteomic screening identifies megakaryocyte-derived PF4/Cxcl4 as a critical driver of myelofibrosis
Capitanio, Daniele, 2023, "Replication Data for Proteomic screening identifies megakaryocyte-derived PF4/Cxcl4 as a critical driver of myelofibrosis", https://doi.org/10.13130/RD_UNIMI/RI3IDJ, UNIMI Dataverse, V2, UNF:6:EIynqsgx5iLtwL7IRdTYTg== [fileUNF]
This dataverse include the LC-MS/MS proteomics datasets of changed proteins generated in the study: "Proteomic screening identifies megakaryocyte-derived PF4/Cxcl4 as a critical driver of myelofibrosis" by Daniele Capitanio, Francesca R. Calledda, Vittorio Abbonante, Daniele Catt... |
Feb 15, 2024 - Quantum Rates
Martinazzo, Rocco, 2024, "Linear Coupling Model", https://doi.org/10.13130/RD_UNIMI/BFQ87D, UNIMI Dataverse, V1
Results from quantum rate calculations of dissipative tunneling rates for a linear coupling model. |
Feb 15, 2024 - Quantum Rates
Martinazzo, Rocco, 2024, "NonLinear Coupling Model A", https://doi.org/10.13130/RD_UNIMI/WCZXRK, UNIMI Dataverse, V1
Dissipative tunneling rates and correlation function details for a non-linear coupling model (Model A) |
Feb 15, 2024 - Quantum Rates
Martinazzo, Rocco, 2024, "NonLinear Coupling Model B", https://doi.org/10.13130/RD_UNIMI/WHRHCT, UNIMI Dataverse, V1
Dissipative tunneing rates and correlation function details for a non-linear coupling model (Model B) |
Feb 14, 2024 - WP4: Platform development
Bitan, Amir, 2024, "Deliverable 4.06 extraction of bio-accessible fractions", https://doi.org/10.13130/RD_UNIMI/MNLT9V, UNIMI Dataverse, V1, UNF:6:LoLs08zw9j5Jl8fGlP1ycA== [fileUNF]
The following dataset includes data, images and text orientated from the work performed in IOLR related to: D 4.6: Optimized extraction of the bio-accessible fractions from feed pellets (submitted 31.03.2022) and Effect of digesta on cell monolayer permeability as described in An... |
Feb 13, 2024 - MADFORWATER-WP3
Mapelli, Francesca, 2020, "Replication data for “Unveiling the microbiota diversity of the xerophyte Argania spinosa L. Skeels root system and residuesphere”", https://doi.org/10.13130/RD_UNIMI/JAG2BM, UNIMI Dataverse, V2, UNF:6:biazmBDg3c1I5d1zuFLYyA== [fileUNF]
This dataset includes results related to the characterization of the bacterial diversity associated to the root system and the residuesphere (litter) of the xerophilic species Argania spinosa |
Feb 12, 2024 - ISLab
Bassani, Alessandra; Del Bo, Beatrice; Ferrara, Alfio; Mangini, Marta; Picascia, Sergio; Stefanello, Ambra, 2024, "LiMe - Liber sententiarum potestatis Mediolani", https://doi.org/10.13130/RD_UNIMI/EN2TFH, UNIMI Dataverse, V1
LiMe is a collection of 325 documents, consisting not only of criminal sentences, but also of many additional notes gathered from the first manuscript of the “Libri sententiarum potestatis Mediolani” (1385-1429), the oldest known registers of criminal sentences for the city of Mi... |
Feb 8, 2024 - Standard Operating Procedures
Pavlovic, Radmila; Ribeiro, Ricardo; Szabó, Anna; Bitan, Amir; Kortner, Trond; Rebecca, Heavyside, 2020, "FISH-AI Standard Operating Procedures", https://doi.org/10.13130/RD_UNIMI/MW6R2N, UNIMI Dataverse, V9
This dataset contains SOPs that have been developed and shared among FISH-AI partners |
Feb 7, 2024 - Heavy Metal Bio-recovery and Valorization
Zecchin, Sarah, 2024, "Heavy Metals-transforming strains characterization", https://doi.org/10.13130/RD_UNIMI/TD9T4C, UNIMI Dataverse, V1
This dataset includes data related to the characterization of bacterial strains able to transform heavy metals. |