 |
ISBN
| 9781482258592 | |
DDC
| 572.8 | |
Tác giả CN
| Moses, Alan M. | |
Nhan đề
| Statistical modeling and machine learning for molecular biology / Alan Moses | |
Thông tin xuất bản
| Boca Raton : Chapman and Hall/CRC, 2017. | |
Mô tả vật lý
| 264 pages. : illustrations ; 24 cm. | |
Tùng thư
| Chapman and Hall/CRC mathematical & computational biology series. | |
Phụ chú
| Includes index. | |
Tóm tắt
| Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics. | |
Thuật ngữ chủ đề
| Molecular biology-Data processing | |
Thuật ngữ chủ đề
| Molecular biology-Statistical methods | |
Khoa
| Khoa Công nghệ Thông tin | |
Khoa
| Khoa Công nghệ sinh học | |
Địa chỉ
| 300Q12_Kho Mượn_02(1): 072485 |
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| 008 | 200925s2017 flu eng |
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| 009 | 1 0 |
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| 020 | |a9781482258592|c1617000 |
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| 082 | |a572.8|bM9111|223 |
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| 100 | |aMoses, Alan M. |
|---|
| 245 | |aStatistical modeling and machine learning for molecular biology / |cAlan Moses |
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| 260 | |aBoca Raton : |bChapman and Hall/CRC, |c2017. |
|---|
| 300 | |a264 pages. : |billustrations ; |c24 cm. |
|---|
| 490 | |aChapman and Hall/CRC mathematical & computational biology series. |
|---|
| 500 | |aIncludes index. |
|---|
| 520 | |aMolecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics. |
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| 541 | |aMua |
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| 650 | |aMolecular biology|xData processing |
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| 650 | |aMolecular biology|xStatistical methods |
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| 690 | |aKhoa Công nghệ Thông tin |
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| 690 | |aKhoa Công nghệ sinh học |
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| 852 | |a300|bQ12_Kho Mượn_02|j(1): 072485 |
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| 890 | |a1|b0|c0|d0 |
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