Cell Research编辑李ds同学要笑了

笑的睡不着觉

以 review 拉动影响因子的策略还是很正确滴，李同学聪明人啊. 这不，还创建了第二本国际学术期刊 Journal of Molecular Cell Biology (JMCB), 具体可以看我以前写的一篇英文文章.

关于 JMCB, 我师兄说, 既然Cell Research 影响因子这么高了,还折腾啥, 这就是李童鞋的高明之处啦,哈哈哈. 成功是可以快速克隆滴, 我在那篇文章里也提到了, JMCB 的第一篇文章就是 reviw,哈哈… 相信被ISI收录后, JMCB影响因子也会很快有.

在一次会议里, 李童鞋说, 在中国本土成功创办一本学术期刊是他的梦想. 正如我的主页的域名, 每个人都应该怀揣梦想.

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美国马里兰 J Craig Venter 研究所 Craig Venter 博士

该世界上第一列人造生命体将以合成细菌的形式首次展示合成生命技术的可行性。研究的大致思路是通过 DNA 转移技术将细菌的基因组移植到与之在进化树上关系很远的酵母体内，经过遗传改造后再将改造基因组转移到另一种细菌体内，这种新型细菌的生长存活正常。

遗传改造的基因组从一细菌转移至另一细菌 （J. Craig Venter 研究所）

dreamfree 语，这也就暗示了未来可以将遗传改造基因或基因组转移到细胞体内，重构新的生命体形式。但是这种完全“人工制造”的基因组在细胞体内究竟会不会按照预想产生最终的器官或生命体甚至更高级的多细胞生物体还有待商榷。 (消息来源: Mail Online, 论文出处: Science DOI: 10.1126/science.1173759)

PS:  这是一篇尝试性日志，打开博客首页，看浏览器标题栏博客名称已经稍作改变，嘿嘿。博客定位：睡到自然醒blog – 生物科普医药健康个人网站。以后不会写不痛不痒的所谓技术性文章，因为我的专业是生物，因为偶不是技术男，哈~ 这也是上次博客满 500 篇日志的一些思考， 其实这个博客初衷就是博客描述所示 — “生物| 生命科学| 医药健康| 科普| 分享| 学习| 交流| 博客|个人网站|”，可一直没碰那方面的话题，或者可能只集中在后者 — “| 博客|个人网站|”，现在考虑话题前倾。也算是这次博客搬家的转折吧，如果大家觉得不合适，也会考虑在换一个域名重新起家，可不大想，那样重新来感觉比较痛苦。欢迎写下你的想法和意见！

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晚上已经在诺贝尔奖官方网站上看到了今年诺贝尔生物学奖得主，当时看的时候网站还没上传获奖得主头像。看来诺贝尔奖的评审及公布程序真的很严格，也许这些诺贝尔生物奖获得者图像是刚刚拍摄采集的呢。

据诺贝尔奖官方网站消息，10月6日当地时间上午11时30分左右(北京时间17时30分左右)，瑞典皇家科学院诺贝尔奖委员会宣布将2008年度诺贝尔生理学或医学奖授予授予德国科学家楚尔郝森和两位法国科学家巴雷-西诺希和路克-蒙塔尼埃。德国科学家因发现人乳头淋瘤病毒引发子宫颈癌获此殊荣，两名法国科学家因发现人类免疫缺陷病毒(HIV)获此殊荣。

楚尔郝森1936年出生于德国，他现在是德国海德堡癌症研究中心的研究人员。雷-西诺希和路克-蒙塔尼埃分别出生于1947年和1932年。楚尔郝森将获得一半的奖金，巴雷-西诺希和路克-蒙塔尼埃将共享另一半奖金。 (中国网)

http://www.dreamfreeblog.com/2008-nobel-prize-physiology-medicine-biology-323.html

The Nobel Prize in Physiology or Medicine 2008

Photo: Magunia/SCANPIX	Photo: L. Dolega/SCANPIX	Photo: DKFZ/SCANPIX
Harald zur Hausen	Françoise Barré-Sinoussi	Luc Montagnier
1/2 of the prize	1/4 of the prize	1/4 of the prize
Germany	France	France
German Cancer Research Centre Heidelberg, Germany	Regulation of Retroviral Infections Unit, Virology Department, Institut Pasteur Paris, France	World Foundation for AIDS Research and Prevention Paris, France
b. 1936	b. 1947	b. 1932

Titles, data and places given above refer to the time of the award.
Photos: Copyright © The Nobel Foundation

http://nobelprize.org/nobel_prizes/medicine/laureates/2008/

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Hedgehog (Hh)蛋白家族调控细胞生长，细胞存活，细胞命运决定等脊椎动物几乎所有模式形成过程的各个方面。单独的一种形态发生子(morphogen)能产生这么广泛的影响是可能的，因为细胞对Hedgehog信号通路的响应依赖于不同细胞种类、接收到的Hedgehog信号剂量强度、以及相应Hedgehog信号的具体时间。

并且Hedgehog的信号梯度由加工、分泌、运输Hedgehog信号所需蛋白特化。细胞响应机制又协同负反馈循环进一步微调Hedgehog信号。影响到Hedgehog信号转导途径的生殖细胞突变体往往伴随发育过程紊乱，同时，激活Hedgehog信号转导通路的体细胞突变往往伴随多种人类癌症的发生。

这篇综述详细介绍了最新Hedgehog信号转导途径研究进展，阐述了Hedgehog信号转导通路的发生机制及发育生物学功能。另外，本综述也讨论了人类疾病发生的病理生物学过程，以探寻人类疾病的潜在治疗方法。

http://www.dreamfreeblog.com/hedgehog-functions-and-mechanisms-316.html

GENES & DEVELOPMENT 22:2454-2472, 2008
©2008 by Cold Spring Harbor Laboratory Press; ISSN 0890-9369/ $5.00
OPEN ACCESS ARTICLE
This Article
OPEN ACCESS ARTICLE

REVIEW

Hedgehog: functions and mechanisms
Markku Varjosalo and Jussi Taipale1

Department of Molecular Medicine, National Public Health Institute (KTL), and Genome-Scale Biology Program, Biomedicum Helsinki, Institute of Biomedicine and High Throughput Center, Faculty of Medicine, University of Helsinki, Helsinki FI-00014, Finland

The Hedgehog (Hh) family of proteins control cell growth, survival, and fate, and pattern almost every aspect of the vertebrate body plan. The use of a single morphogen for such a wide variety of functions is possible because cellular responses to Hh depend on the type of responding cell, the dose of Hh received, and the time cells are exposed to Hh. The Hh gradient is shaped by several proteins that are specifically required for Hh processing, secretion, and transport through tissues. The mechanism of cellular response, in turn, incorporates multiple feedback loops that fine-tune the level of signal sensed by the responding cells. Germline mutations that subtly affect Hh pathway activity are associated with developmental disorders, whereas somatic mutations activating the pathway have been linked to multiple forms of human cancer. This review focuses broadly on our current understanding of Hh signaling, from mechanisms of action to cellular and developmental functions. In addition, we review the role of Hh in the pathogenesis of human disease and the possibilities for therapeutic intervention.

[Keywords: hedgehog; signal transduction; cancer; development; transcription]

1 Corresponding author.

http://genesdev.cshlp.org/cgi/content/abstract/22/18/2454

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世界大学科研论文质量评比:2008世界科研论文排名
HEEACT Ranking-2008世界大学科研论文质量评比排名英文原文

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有些读者发信询问是否有英文原文或者什么PDF格式下载，看来大家对这个排名还是很感兴趣的。很简单，今天到「世界大学科研论文质量评比」系统官方网站HEEACT ranking进行查询。

ranking review in english

2008 Performance Ranking of Scientific Papers for World Universities 

Methodology

This project employs bibliometric methods to analyze and rank the scientific
papers performances of the top 500 universities in the world. The selection of
the 500 universities for inclusion in this project is primarily based on
information obtained from the Essential Science Indicators (ESI). Of the more
than 3,000 research institutions listed in ESI, this project selects the top 700
institutions sorted by the numbers of published journal articles. Exclusion of
non-university institutions from the primary list and the comparison to the
lists of universities included in the other ranking programs resulted in the 700
universities in this project. Data used to assess the performances of the
universities is drawn from ISI’s ESI, Web of Science (WOS), which includes SCI
and SSCI, and Journal Citation Reports (JCR).

The concept of authority control is employed to retrieve data indexed under
different forms of a university’s name in those resources – i.e., the official
name, the abbreviated and other possible forms of the names. This project also
considers the mergers and splitting of universities (or different campuses in a
university system) and includes publications by a university’s affiliated
institutions such as research centers and university hospitals. This effort
ensures the accuracy of each university’s number of published journal articles
and the subsequent statistics of their citations.
 
Indicators
The 2008 performance measures are composed of eight indicators. One indicator
used in the 2007 ranking (“number of subject fields where the university shows
excellence”) has been removed and the weightings of the 2008 indicators have
been adjusted accordingly. The indicators together represent three different
criteria of scientific papers performance: research productivity, research
impact, and research excellence. Table 1 lists the indicators and shows their
respective weightings for the indicators.
 
Table 1: The Criteria, Indicators, and Their Respective Weightings Used for the
Overall Performance Based Ranking
      Criteria2008 Overall Performance IndicatorsWeighting
      Research productivityNumber of articles of the last 11 years
      (1997-2007)1020
      Number of articles of the current year (2007)10
      Research impactNumber of citations of the last 11 years (1997-2007)1030
      Number of citations of the last 2 years (2006-2007)10
      Average number of citations of the last 11 years (1997-2007)10
      Research excellenceH-index of the last 2 years (2006-2007)2050
      Number of Highly Cited Papers (1997-2007)15
      Number of articles of the current year in high-impact journals (2007)15

 
Research Productivity:
 
The number of articles published in peer-reviewed academic journals is an
appropriate indicator of the productivity of a research institution. To fairly
represent a university’s on-going and current research productivity, this
project employs two indicators: the number of articles in the last eleven years
(1997-2007), and the number of articles in the current year (2007).

“Number of articles in the last 11 years” draws data from ESI, which include
1997-2007 statistics of articles published in journals indexed by SCI and SSCI.
“Number of articles in the current year” relies on the 2007 data obtained from
SCI and SSCI, which were searched between Jan 19 and Jan 31, 2008.
 
Research Impact:
 
The number of citations on a particular academic article within a specific time
frame is a commonly accepted indicator for that article’s impact. This project
considers both the long-term and short-term impacts of a particular research and
seeks to provide a fair representation of a university’s research impact
regardless of its size and faculty number.  Thus, this project measures research
impact by: the number of citations in the last eleven years, the number of
citations in the last two years, and the average number of citations in the last
eleven years.

“Number of citations in the last 11 years” draws 1997-2007 citation statistics
from ESI. “Number of citations in the last 2 years” draws 2006-2007 citation
statistics from SCI and SSCI at WOS, which include citation statistics updated
to the dates of retrieval. “Average number of citations in the last 11 years” is
the number of articles in the last eleven years divided by the number of
citations in the last eleven years.
 
Research Excellence:
 
 This project assesses each university’s research excellence by the following
indicators: the h-index of the last two years, the number of Highly Cited Papers
from ESI, and the number of articles in high-impact journals in the current year
(Hi-Impact journal articles). “H-index of the last 2 years” measures both the
quantity and quality of a university’s research via the use of the 2006-2007
data from SCI and SSCI. It is defined as “a university has index h if h of its
Np papers in the last two years have at least h citations each and the other (Np
– h) papers have ≦h citations each”.

“Number of Highly Cited Papers” utilizes data from ESI, which include statistics
of “Highly Cited Papers” from 1997 to 2007. ESI defines Highly Cited Papers as
SCI /SSCI-indexed papers that are cited most (in the top 1% of the total papers
indexed in the same year) within the last 11 years.

“Number of articles of the current years in high-impact journals” employs data
from JCR, which supplied the impact factor of each journal in its subject field.
The impact factor of a journal is the number of citations to the papers
published in that particular journal within the previous two years divided by
the number of that journal’s papers within the previous two years. A journal
with a higher impact factor means its articles are more frequently cited by
other journals, thus suggesting its higher scholarly value. This project defines
high-impact journals as journals whose impact factors are ranked as the top 5%
of the total journals within a specific subject category. With high-impact
journals lists derived from JCR, this project is able to count the numbers of
each university’s articles published in high-impact journals by subject.
 
Data Processing
 The procedures for data processing are as follow. First, the project staff
conducts authority control on the various forms of a university name and
analyzes all the SCI/SSCI bibliographic records in which the address field
contained one of the forms of the university name. An accurate number of the
total articles from a university are obtained after removing duplicate records
containing different forms of that university’s name. Second, using SCI/SSCI,
this project obtains the total number of citations by adding the number of
citations on each of the articles from that university from its inclusion in
SCI/SSCI to the date of retrieval for this research.

 Some university systems have several campuses. A few campuses within a
particular university system may have been commonly perceived as individual
institutions. However, they are indexed in ESI only by the university system
name. For example, University of Wisconsin-Madison and University of
Wisconsin-Milwaukee are not differentiated in ESI (they are both indexed under
“Univ Wisconsin”) though they are often perceived as two individual
universities. This project corrects the flaw by manually searching SCI/SSCI in
order to identify the actual number of articles and citations of these articles
produced by each individual campus. Likewise, this project employs the same
manual searching procedures to ensure the measurement of each university’s
Highly Cited Papers have fairly represented the research performance of each
individual university campus.
 
Score Calculation and Sorting
 Based on the measurement procedures, this project calculates a university’s
score for each of the eight indicators. For each indicator, the university with
the highest number receives the maximum points (100); the other universities’
numbers are subdivided by the highest number and are converted decimally into
their respective scores. For example, if University A has the highest number M
for Indicator X, it receives 100 for that indicator, while University B with a
number of N receives (N/M×100) for that particular indicator. Finally, the
project calculates the final score of each university by the indicator
weightings presented in Table 1 and sorts the universities by their final
scores. Universities with the same scores are sorted alphabetically. It should
be noted that many universities obtain similar scores, and the slight
differences of the final scores must be interpreted carefully. A university’s
slightly higher score than another university’s may not necessarily suggest its
superiority in scientific research because the two universities might be in very
close proximity in the ranking.
 
Copyright © 2007 Higher Education Evaluation and Accreditation Council of Taiwan 

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这项评比推出后深受国际重视，将HEEACT Ranking与上海交大、英国时报高等教育增刊、西班牙世界大学网路排名的三大全球大学排名系统并列讨论，澳洲国家教育部更公开参考采用。

2008年世界大学科研论文不分领域的前五百大排名，美国就占一百六十三校，并包办前十一名，依序为哈佛大学、约翰霍普金斯大学、史丹福大学、华盛顿大学西雅图分校、加州大学洛杉矶分校、加州大学柏克莱分校、密西根大学安娜堡分校、麻省理工学院、加州大学旧金山分校、加州大学圣地牙哥分校、宾州大学。

前五百大的不分领域排名中，亚洲地区由日本三十五校居冠，日本东京大学排名第十二；其次为中国大陆十三校，再来为香港与台湾各五校。

分领域排名方面。台湾共有台大、成功、清华、交通、中央大学、中山大学、台湾科大、中兴大学等八所大学在工科领域 。台大、清华、成功、交通四校在理科领域 。台大、中兴两校在农学领域 。台大、阳明两校在临床医学领域 。台大一校在生命科学领域分别进入世界前三百强。而社会科学领域则没有学校进榜。

分析华人地区大学表现，绝大多数排名进步，其中新加坡国立大学 (86名，去年96名)进入世界百大，台湾大学则超越香港大学，跃升为两岸三地第一 (141名，去年185名)，其次为北京清华大学 (152名，去年250名)、北京大学 (164名，去年241名)及香港大学 (173名，去年182名)。 via

相关阅读：Cell-Science in China: 30 Years On,细胞杂志撰文:中国科学三十年

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英文摘要：

Xin Hao  (Seattle, WA, USA)

改革开放三十年，中国在许多方面取得了巨大进步，包括科学和教育。比如，支持基础研究的国家自然科学基金会，从1986年成立以来，经费预算平均每年上涨22% ，今年达7.86亿美元。已经有迹象表明中国人才流失的现象可能逆转。几位顶尖的旅居国外的科学家，如芝加哥西北大学的神经科学家饶毅和普林斯顿大学的结构生物学家施一公放弃了他们在美国的终身职位回国，分别领导北京大学生命科学学院和清华大学生物学系。去年，无党派人士、科学家兼医生陈竺被任命为卫生部长。中国科学院院士、复旦大学的杨雄里说：“我告诉在美国的学生，现在该回国了”。但是中国的生命科学研究要想具备国际竞争力还面临不少挑战。

1980年，康奈尔大学的遗传学家吴瑞在阔别中国31年后第一次回国。他向中国教育部提出建议，建立中美生物化学和分子生物学联合招生计划（CUSBEA）。这个计划在1981年到1989年间共输送了425名学生到美国攻读生命科学博士学位。生物化学家王晓东是这批人的代表，他是改革开放三十年来第一位当选美国科学院院士的大陆学生。他现在兼任北�生命科学研究所所长。CUSBEA的成功也为其他许多中国学生到美国进行深造打开了大门。

1985年到2005年，约有一万两千中国学生获得生物、医学、农业和其它生命科学博士学位。2007年研究发现，92%的中国博士学位获得者留在美国。以施一公为主席的北美华人生物学家协会估计美国有两千五百到三千中国教授。过去十年中国政府曾经发起数个计划试图吸引留学生回国，结果好坏参半。

为了增加年轻科学家的数量，教育部所属的中国留学中心去年开始一个新计划，在五年中耗资13亿美元，每年从中国顶尖大学中选拔5000名学生留学西方。生命科学是其中的重点支持学科。有些中国科学家对这个计划表示担忧。饶毅说，“我对这个计划很困惑。好学生自己就可以出国，不用政府资助。经费用来支持国内研究生更好。他们的工资太低了”。去年他们回国不久，饶毅、施一公等起草了一封信，征集了五十多个教授签名，建议政府提高研究生待遇。中国总理******已经同意此建议，据悉政府有关部门正在讨论实施细节。

与缺少优秀研究生并存的问题是博士后的严重缺乏。最近从耶鲁大学招聘到南开大学做生命科学学院院长的尹芝南说，“对于回国的科学家来说，最大的问题是没有博士后”，“很明显，美国的工资有优势”。杨雄里也同意这个说法，“我培养的研究生都出国做博士后了”。尹芝南强调说，“中国应该大幅度提高博士后的工资”。

科学家们都认为，中国的经费分配体制和研究评估机制需要进行改革。“经费本身不再是主要问题”，饶毅说，“问题是评估和分配体制”。施一��和饶毅意见相同，并称现行体制“压抑创新”。中国经济改革的前二十年里，国家强调应用研究，忽视基础研究。其后，基础研究的投入增加不少，“尤其是在最近五年”，复旦的杨雄里说。尽管如此，增加以后的基础科学经费只占研发经费的5%，而日本是15%，美国是19%。中国政府给体育的投入高于基础研究。另一个问题是过度依赖SCI文章和影响因子作为评估科学家及其研究水平的指标。杨雄里说，“发表文章的压力使得科学家们选择更容易的课题以迅速出产论文成果。”

Science in China: 30 years on  PDF (523K) 下载，有趣的可以看看原文。

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由此种方法预测重建的蛋白互作网络含40753种互作关系，2259种蛋白质参与，并形成了16个互相链接的主节点。除了同型二聚体(homodimers)，所有的MIPS复合体均被成功整合到预测网络中。其中，约35%的复合体鉴定表现为互相连接，另外7中蛋白复合体可能和上述复合体功能相关。

因此，这种分析方法为以高置信GO为基础的注释方法完全测序的基因组提供新的蛋白质-蛋白质互相作用图谱。

文献阅读：
Prediction of yeast protein–protein interaction network: insights from the Gene Ontology and annotations
Xiaomei Wu, Lei Zhu, Jie Guo, Da-Yong Zhang and Kui Lin*

MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University Beijing 100875, China
Nucleic Acids Research 2006 34(7):2137-2150; doi:10.1093/nar/gkl219

A map of protein–protein interactions provides valuable insight into the cellular function and machinery of a proteome. By measuring the similarity between two Gene Ontology (GO) terms with a relative specificity semantic relation, here, we proposed a new method of reconstructing a yeast protein–protein interaction map that is solely based on the GO annotations. The method was validated using high-quality interaction datasets for its effectiveness. Based on a Z-score analysis, a positive dataset and a negative dataset for protein–protein interactions were derived. Moreover, a gold standard positive (GSP) dataset with the highest level of confidence that covered 78% of the high-quality interaction dataset and a gold standard negative (GSN) dataset with the lowest level of confidence were derived. In addition, we assessed four high-throughput experimental interaction datasets using the positives and the negatives as well as GSPs and GSNs. Our predicted network reconstructed from GSPs consists of 40 753 interactions among 2259 proteins, and forms 16 connected components. We mapped all of the MIPS complexes except for homodimers onto the predicted network. As a result, 35% of complexes were identified interconnected. For seven complexes, we also identified some nonmember proteins that may be functionally related to the complexes concerned. This analysis is expected to provide a new approach for predicting the protein–protein interaction maps from other completely sequenced genomes with high-quality GO-based annotations.

延伸阅读:

• 研究蛋白质与蛋白质相互作用方法总结-实验步骤 (1)
• 检测两种蛋白质之间相互作用的实验方法比较 (5)
• 基于文本的在线预测蛋白相互作用网站 (3)

下面简单推荐介绍一个蛋白质间相互作用在线预测的网站。不仅可以直接输入文本内容，而且可以上传txt/html/pdf格式的整个文件(注意html/pdf格式论文会产生干扰噪值) ，值得一提的是可以和PubMed形成接口，如直接填入Session ID或PubMed Search 结果的ID。

该蛋白互作信息挖掘系统(Protein Interaction information Extraction system, PIE)主要原理是利用自然语言处理技术和机器识别方法来预测蛋白互作语句，准确度很高。

不过话说回来，我想文献毕竟是人写的，有时甚至晦涩难懂，可能还需要一定的人为参与校正吧，经过人高级的大脑系统地重新整理编译才真正可靠，提高可信度。

蛋白互作在线预测网站：http://bi.snu.ac.kr/pie/
韩国的一个生物智能实验室(Biointelligence Lab)。

更多信息参考下面这篇文献：
Nucleic Acids Res. 2008 July 1; 36(Web Server issue): W411–W415.
Published online 2008 July 1. doi: 10.1093/nar/gkn281.
PIE: an online prediction system for protein–protein interactions from text  pdf

延伸阅读:

• 酵母蛋白质相互作用网络预测方法 (7)
• 研究蛋白质与蛋白质相互作用方法总结-实验步骤 (1)
• 检测两种蛋白质之间相互作用的实验方法比较 (5)