《生物化学与生物物理进展》征稿简则(2020年12月修订)

1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.1.2栏目设置本刊设有综述与专论、研究快报、研究报告、技术与方法、新技术讲座、科教融合.     

多组学技术及其在生命科学研究中应用概述

随着新一代测序技术、高分辨质谱技术、多组学整合分析方法及数据库的发展,组学技术正从传统的单一组学向多组学技术发展。以多组学驱动的系统生物学研究将带来生命科学研究的新范式。本文简要概述了基因组学、表观基因组学、转录组学,蛋白质组学及代谢组学的进展,重点介绍多组学技术平台的组成和功能,多组学技术的应用现状及在合成生物学及生物医学等领域的应用前景。     

《生物化学与生物物理进展》征稿简则

(2020年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

《生物化学与生物物理进展》征稿简则(2020年12月修订)

(2020年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

《生物化学与生物物理进展》征稿简则

正(2016年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

《生物化学与生物物理进展》征稿简则

正(2017年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

《生物化学与生物物理进展》征稿简则

正(2020年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

《生物化学与生物物理进展》征稿简则

(2011年12月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.1.2栏目设置     

《生物化学与生物物理进展》征稿简则

正(2019年1月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关     

《生物化学与生物物理进展》征稿简则

<正>(2019年1月修订)1征稿范围与栏目设置1.1征稿范围本刊为国内外公开发行的全国性学术期刊,月刊,每月20日发行.征稿的学科范围是生物化学、分子生物学、生物物理学、细胞生物学、神经科学、免疫学,以及基因组学、蛋白质组学、系统生物学等相关学科领域.     

生理学与基因组学:走向系统生物学

近十年来,生理学与基因组学达到了空前的融合。尽管生理基因组学还是一个非常年轻的研究领域,系统生物学概念的引入必将推进生理基因组学达到全新的水平。本文概要地叙述了这个令人振奋的生理科学的新时代给生理学家带来的机遇和挑战,并以我们自己近十年来的经验为例,讨论了怎样通过扩展和延伸生理学与基因组学的结合,从而对生物学得到系统的理解。     

From proteomes to complexomes in the era of systems biology

Protein complexes carry out almost the entire signaling and functional processes in the cell. The protein complex complement of a cell, and its network of complex–complex interactions, is referred to here as the complexome. Computational methods to predict protein complexes from proteomics data, resulting in network representations of complexomes, have recently being developed. In addition, key advances have been made toward understanding the network and structural organization of complexomes. We review these bioinformatics advances, and their discovery‐potential, as well as the merits of integrating proteomics data with emerging methods in systems biology to study protein complex signaling. It is envisioned that improved integration of proteomics and systems biology, incorporating the dynamics of protein complexes in space and time, may lead to more predictive models of cell signaling networks for effective modulation.     

Cell biology, chemogenomics and chemoproteomics

The scientific techniques used in molecular biological research and drug discovery have changed dramatically over the past 10 years due to the influence of genomics, proteomics and bioinformatics. Furthermore, genomics and functional genomics are now merging into a new scientific approach called chemogenomics. Advancements in the study of molecular cell biology are dependent upon "omics" researchers realizing the importance of and using the experimental tools currently available to cell biologists. For example, novel microscopic techniques utilizing advanced computer imaging allow for the examination of live specimens in a fourth dimension, viz., time. Yet, molecular biologists have not taken full advantage of these and other traditional and novel cell biology techniques for the further advancement of genomic and proteomic-oriented research. The application of traditional and novel cellular biological techniques will enhance the science of genomics. The authors hypothesize that a stronger interdisciplinary approach must be taken between cell biology (and its closely related fields) and genomics, proteomics and bio-chemoinformatics. Since there is a lot of confusion regarding many of the "omics" definitions, this article also clarifies some of the basic terminology used in genomics, and related fields. It also reviews the current status and future potential of chemogenomics and its relationship to cell biology. The authors also discuss and expand upon the differences between chemogenomics and the relatively new term--chemoproteomics. We conclude that the advances in cell biology methods and approaches and their adoption by "omics" researchers will allow scientists to maximize our knowledge about life.     

Network genomics – A novel approach for the analysis of biological systems in the post-genomic era

Network Genomics studies genomics and proteomics foundations of cellular networks in biological systems. It complements systems biology in providing information on elements, their interaction and their functional interplay in cellular networks. The relationship between genomic and proteomic high-throughput technologies and computational methods are described, as well as several examples of specific network genomic application are presented.