Network Bioscience, 2nd Edition
Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate...
Saved in:
| Format: | Online |
|---|---|
| Language: | English |
| Published: |
Frontiers Media SA
2021
|
| Subjects: | |
| Online Access: | ONIX_20211118_9782889636501_924 |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1869527208825978880 |
|---|---|
| collection | Directory of Open Access Books |
| description | Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of ‘big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein–protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing’. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks. |
| format | Online |
| id | doab-20.500.12854ir-73792 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
| record_format | ojs |
| spelling | doab-20.500.12854ir-737922024-04-04T19:19:44Z Network Bioscience, 2nd Edition Pellegrini, Marco Antoniotti, Marco Mishra, Bud systems biology network science network biology cancer networks hypothesis generation and verification computational biology thema EDItEUR::P Mathematics and Science::PD Science: general issues thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of ‘big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein–protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing’. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks. 2021-11-18T16:24:51Z 2021-11-18T16:24:51Z 2020 book ONIX_20211118_9782889636501_924 9782889636501 https://directory.doabooks.org/handle/20.500.12854/73792 eng image/jpeg Attribution 4.0 International https://www.frontiersin.org/research-topics/7394/network-bioscience https://www.frontiersin.org/research-topics/7394/network-bioscience Frontiers Media SA 10.3389/978-2-88963-650-1 10.3389/978-2-88963-650-1 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889636501 270 open access |
| spellingShingle | systems biology network science network biology cancer networks hypothesis generation and verification computational biology thema EDItEUR::P Mathematics and Science::PD Science: general issues thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics Network Bioscience, 2nd Edition |
| title | Network Bioscience, 2nd Edition |
| title_full | Network Bioscience, 2nd Edition |
| title_fullStr | Network Bioscience, 2nd Edition |
| title_full_unstemmed | Network Bioscience, 2nd Edition |
| title_short | Network Bioscience, 2nd Edition |
| title_sort | network bioscience 2nd edition |
| topic | systems biology network science network biology cancer networks hypothesis generation and verification computational biology thema EDItEUR::P Mathematics and Science::PD Science: general issues thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics |
| topic_facet | systems biology network science network biology cancer networks hypothesis generation and verification computational biology thema EDItEUR::P Mathematics and Science::PD Science: general issues thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics |
| url | ONIX_20211118_9782889636501_924 |