| Judul | Predicting Transcription Factor Complexes / Thorsten Will |
| Pengarang | Will, Thorsten |
| Penerbitan | Wiesbaden : Springer Fachmedien Wiesbaden, 2015 |
| Deskripsi Fisik | xix, 142 p. :ilus. ;21 cm |
| ISBN | 978-3-658-08269-7 |
| Subjek | BIOINFORMATICS COMPUTER APPL. IN LIFE SCIENCES MATHEMATICAL AND COMPUTATIONAL BIOLOGY |
| Catatan | In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation. |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
http://link.springer.com/openurl?genre=book&isbn=978-3-658-08268-0 |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 192815292 | 578.6 Wil p | Baca di tempat | Perpustakaan Pusat - Online Resources Ebook |
Tersedia |
| Tag | Ind1 | Ind2 | Isi |
| 001 | INLIS000000000163043 | ||
| 005 | 20250627065242 | ||
| 007 | ta | ||
| 008 | 250627################|##########|#|## | ||
| 020 | # | # | $a 978-3-658-08269-7 |
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| 082 | # | # | $a 578.6 |
| 084 | # | # | $a 578.6 Wil p |
| 100 | 1 | # | $a Will, Thorsten |
| 245 | 1 | # | $a Predicting Transcription Factor Complexes /$c Thorsten Will |
| 260 | # | # | $a Wiesbaden :$b Springer Fachmedien Wiesbaden,$c 2015 |
| 300 | # | # | $a xix, 142 p. : $b ilus. ; $c 21 cm |
| 505 | # | # | $a In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation. |
| 650 | # | # | $a BIOINFORMATICS |
| 650 | # | # | $a COMPUTER APPL. IN LIFE SCIENCES |
| 650 | # | # | $a MATHEMATICAL AND COMPUTATIONAL BIOLOGY |
| 856 | # | # | $a http://link.springer.com/openurl?genre=book&isbn=978-3-658-08268-0 |
| 990 | # | # | $a 192815292 |
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