歐洲分子生物學實驗室下屬的歐洲生物信息學研究所（EMBL-EBI）,，與遍布世界的30個實驗室一起聯(lián)合發(fā)布了一套用圖表表示生物學信息的新標準,。如同電子學中的電路圖一樣，該套標準圖表的應用將會使生物學研究領(lǐng)域中復雜信息的交流更加容易,，使模型變得準確,、高效和容易理解。新標準稱為系統(tǒng)生物學圖釋（SBGN）,，發(fā)表在近期出版的《自然·生物技術(shù)》雜志上,。
標準化的圖表，做為一種視覺語言,，被廣泛應用于多個學科領(lǐng)域,。使用標準圖表法傳達復雜信息，表意清晰,、易于理解,。但在圖表信息占據(jù)重要地位的生物學領(lǐng)域，卻一直沒有統(tǒng)一的標準圖表描述所有的生物化學反應,、路徑和網(wǎng)絡,。
2005年,，各國的研究人員開始努力開發(fā)一種專門用于分子和系統(tǒng)生物學研究的新圖表標準，即SBGN項目,。該項目由日本東京系統(tǒng)生物學研究所的北野宏明發(fā)起,，英國辛克斯頓歐洲生物信息學研究所的尼古拉斯·勒·諾瓦克和美國加州理工學院的邁克爾·胡克負責協(xié)調(diào)。研究團隊則包括生物化學家,、模型制作人員和計算機科學家,。
勒·諾瓦克指出，在基因組學時代,，特別是高通量技術(shù)出現(xiàn)之后,，生物學數(shù)據(jù)的規(guī)模總量有了大幅度增長,，SBGN會使研究人員更容易了解彼此的模型,，更有效地分享數(shù)據(jù)。它將使眾多的系統(tǒng)生物學家從中受益,，無論他們研究的重點是生化進程中的哪個環(huán)節(jié),。
為了確保新圖表不會變得過于龐大、復雜,，研究人員定義了三種不同類型的圖解,，互相補充，描述分子過程,、實體關(guān)系和生化活動中的各個環(huán)節(jié),。報道稱，SBGN十分簡單,，有眾多研究團體的廣泛參與,，相信這種表示法將會迅速得到廣泛的應用。（生物谷Bioon.com）
生物谷推薦原始出處：
Nature Biotechnology 27, 735 - 741 (2009) 7 August 2009 | doi:10.1038/nbt.1558
The Systems Biology Graphical Notation
Nicolas Le Novère1, Michael Hucka2, Huaiyu Mi3, Stuart Moodie4, Falk Schreiber5,6, Anatoly Sorokin7, Emek Demir8, Katja Wegner9, Mirit I Aladjem10, Sarala M Wimalaratne11, Frank T Bergman12, Ralph Gauges13, Peter Ghazal4,14, Hideya Kawaji15, Lu Li1, Yukiko Matsuoka16, Alice Villéger17,18, Sarah E Boyd19, Laurence Calzone20, Melanie Courtot21, Ugur Dogrusoz22, Tom C Freeman14,23, Akira Funahashi24, Samik Ghosh16, Akiya Jouraku24, Sohyoung Kim10, Fedor Kolpakov25,26, Augustin Luna10, Sven Sahle13, Esther Schmidt1, Steven Watterson4,22, Guanming Wu27, Igor Goryanin4, Douglas B Kell18,28, Chris Sander8, Herbert Sauro12, Jacky L Snoep29, Kurt Kohn10 & Hiroaki Kitano16,30,31
Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.
1 EMBL European Bioinformatics Institute, Hinxton, UK.
2 Engineering and Applied Science, California Institute of Technology, Pasadena, California, USA.
3 SRI International, Menlo Park, California, USA.
4 Centre for Systems Biology at Edinburgh, University of Edinburgh, Edinburgh, UK.
5 Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.
6 Institute of Computer Science, University of Halle, Halle, Germany.
7 School of Informatics, University of Edinburgh, Edinburgh, UK.
8 Memorial Sloan Kettering Cancer Center - Computational Biology Center, New York, NY, USA.
9 Science and Technology Research Institute, University of Hertfordshire, Hatfield, UK.
10 National Cancer Institute, Bethesda, Maryland, USA.
11 Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
12 Department of Bioengineering, University of Washington, Seattle, Washington, USA.
13 BIOQUANT, University of Heidelberg, Heidelberg, Germany.
14 Division of Pathway Medicine, University of Edinburgh Medical School, Edinburgh, UK.
15 Riken OMICS Science Center, Yokohama City, Kanagawa, Japan.
16 The Systems Biology Institute, Tokyo, Japan.
17 School of Computer Science, University of Manchester, Manchester, UK.
18 Manchester Interdisciplinary Biocentre, Manchester, UK.
19 Clayton School of Information Technology, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
20 U900 INSERM, Paris Mines Tech, Institut Curie, Paris, France.
21 Terry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, British Columbia, Canada.
22 Bilkent Center for Bioinformatics, Bilkent University, Ankara, Turkey.
23 The Roslin Institute, University of Edinburgh, Midlothian, UK.
24 Department of Biosciences and Informatics, Keio University, Hiyoshi, Kouhoku-ku, Yokohama, Japan.
25 Institute of Systems Biology, Novosibirsk, Russia.
26 Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia.
27 Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
28 School of Chemistry, University of Manchester, Manchester, UK.
29 Department of Biochemistry, Stellenbosch University, Matieland, South Africa.
30 Sony Computer Science Laboratories, Tokyo, Japan.
31 Okinawa Institute of Science and Technology, Okinawa, Japan.
