找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪(fǎng)問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Data Mining for Systems Biology; Methods and Protocol Hiroshi Mamitsuka,Charles DeLisi,Minoru Kanehisa Book 2013 Springer Science+Business

[復(fù)制鏈接]
樓主: 軍械
21#
發(fā)表于 2025-3-25 05:24:01 | 只看該作者
22#
發(fā)表于 2025-3-25 08:25:25 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2ortant challenge to gain insight on a cell’s working mechanisms. We present SIRENE, a method to estimate a GRN from a collection of expression data. Contrary to most existing methods for GRN inference, SIRENE requires as input a list of known regulations, in addition to expression data, and implemen
23#
發(fā)表于 2025-3-25 13:40:03 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2underlying network. We present a technique addressing this problem through focussing on a more limited problem: inferring direct targets of a transcription factor from short expression time series. The method is based on combining Gaussian process priors and ordinary differential equation models all
24#
發(fā)表于 2025-3-25 19:19:24 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2iological networks. Currently, the most comprehensive and validated biological networks are metabolic networks. Complete metabolic networks are easily sourced from multiple online databases. These databases reveal metabolic networks to be large, highly complex structures. This complexity is sufficie
25#
發(fā)表于 2025-3-25 21:26:24 | 只看該作者
26#
發(fā)表于 2025-3-26 01:35:15 | 只看該作者
27#
發(fā)表于 2025-3-26 06:00:38 | 只看該作者
28#
發(fā)表于 2025-3-26 12:09:58 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2terfaces may lead to the development of many diseases. In this chapter, we will briefly introduce the background knowledge of the protein–protein interaction, followed by the detailed explanation of varied analysis—from basic to advanced, as well as related tools and databases. VisANT (.)—a free Web
29#
發(fā)表于 2025-3-26 16:22:08 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2sts of thousands of databases that were derived through computational inference of metabolic pathways from the MetaCyc pathway/genome database (PGDB). In some cases, these DBs underwent subsequent manual curation. Curated pathway DBs are now available for most of the major model organisms. Databases
30#
發(fā)表于 2025-3-26 17:48:26 | 只看該作者
https://doi.org/10.1007/978-3-663-07869-2already a common procedure in identifying biomarkers or signatures of phenotypic states such as diseases or compound treatments. However, in most of the cases, especially in complex diseases, even given a list of biomarkers, the underlying biological mechanisms are still obscure to us. In other word
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-30 22:44
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
寿阳县| 广昌县| 砚山县| 青龙| 梅河口市| 靖州| 丹凤县| 太康县| 东方市| 象山县| 乌鲁木齐市| 涟源市| 贺州市| 鹤峰县| 墨玉县| 闸北区| 会理县| 康平县| 承德市| 社旗县| 文水县| 内黄县| 潼关县| 凯里市| 彰化县| 雷波县| 达拉特旗| 平遥县| 大石桥市| 宁河县| 襄城县| 中西区| 广平县| 甘南县| 郧西县| 松潘县| 榆林市| 永寿县| 黄平县| 胶州市| 鲁山县|