| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA990007988370403321 |
|
|
Autore |
Ruiz-Tolosa, Juan Ramon |
|
|
Titolo |
From vectors to tensor / J.R. Ruiz-Tolosa, E. Castillo |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Locazione |
|
|
|
|
|
|
Collocazione |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNISA990006048430203316 |
|
|
Autore |
CRISPI, Francesco |
|
|
Titolo |
Lo stato di assedio : discorsi parlamentari / F. Crispi |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Roma : Tipografia della Camera dei Deputati, 1894 |
|
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Crispi, Francesco Discorsi parlamentari |
|
|
|
|
|
|
Collocazione |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
3. |
Record Nr. |
UNINA9910806198703321 |
|
|
Autore |
Roy Kunal <1971-> |
|
|
Titolo |
q-RASAR : A Path to Predictive Cheminformatics / / by Kunal Roy, Arkaprava Banerjee |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2024.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (99 pages) |
|
|
|
|
|
|
Collana |
|
SpringerBriefs in Molecular Science, , 2191-5415 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Chemistry - Data processing |
Quantum theory |
Computer simulation |
Molecules - Models |
Computational Chemistry |
Quantum Simulations |
Molecular Modelling |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references. |
|
|
|
|
|
|
Nota di contenuto |
|
Chemical Information and Molecular Similarity -- Read-across and Quantitative Structure-activity Relationships (QSAR) for Making Predictions and Data Gap-Filling -- Quantitative Read-Across (q-RA) and Quantitative Read-Across Structure-Activity Relationships (q-RASAR) – Genesis and Model Development -- Tools, Applications, and Case Studies (q-RA and q-RASAR) -- Future Prospects. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data gap-filling methods. It discusses the genesis and model development of q-RASAR models demonstrating practical examples. It also showcases successful case studies on the application of q-RASAR modeling in medicinal chemistry, predictive toxicology, and materials sciences. The book also includes the tools used for q-RASAR model development for new users. It is a valuable resource for researchers and students interested in grasping the development algorithm of q-RASAR models and their application within specific research domains. |
|
|
|
|
|
|
|
| |