MOLECULAR PHYLOGENETICS AND EVOLUTION

英文简介

Molecular Phylogenetics and Evolution is dedicated to bringing Darwin's dream within grasp - to "have fairly true genealogical trees of each great kingdom of Nature." The journal provides a forum for molecular studies that advance our understanding of phylogeny and evolution, further the development of phylogenetically more accurate taxonomic classifications, and ultimately bring a unified classification for all the ramifying lines of life. Phylogeographic studies will be considered for publication if they offer EXCEPTIONAL theoretical or empirical advances.The journal encourages articles that are multidisciplinary, especially in areas, such as bioinformatics, computational biology, molecular biology, and organismic biology, that are of interest to the community of systematic and evolutionary biologists. In addition, presentations of new findings on or insights into evolutionary processes and mechanisms as expressed at the molecular level are welcome, as are those that deal with the methodology of reconstructing evolutionary history from molecular data (such as descriptions of new or more powerful computer algorithms for constructing phylogenetic trees from orthologous nucleotide or aminoacid sequences). A deeper understanding of the mechanisms and processes of molecular evolution should lead to more accurate models of molecular evolution, which in turn should facilitate the development of better algorithms for reconstructing evolutionary history from sequence data.Papers based on few taxa, single molecular markers, or that use codon-based methods to test for positive Darwinian selection, but in the absence of experimental evidence that allegedly selected amino acid changes cause an adaptive phenotypic effect, will not be accepted.

中文简介

分子系统遗传学和进化致力于使达尔文的梦想触手可及——“拥有每个大自然王国相当真实的系谱树。”该杂志为分子研究提供了一个论坛，促进我们对系统发育和进化的理解，进一步发展系统发育上更精确的分类，并最终为所有的分支生命线带来统一的分类。如果系统地理学研究提供了特殊的理论或实证进展，将考虑出版。该杂志鼓励多学科的文章，特别是在领域，如生物信息学，计算生物学，分子生物学和有机体生物学，是有兴趣的社区的系统和进化生物学家。此外,报告新发现或见解的进化过程和机制上表达了在分子水平上是受欢迎的,就像那些处理重建从分子进化历史数据的方法(如描述的新的或更强大的计算机算法从同源核苷酸或氨基酸序列构建系统发育树)。对分子进化机制和过程的深入理解，将有助于建立更精确的分子进化模型，从而有助于开发更好的算法，从序列数据重建进化历史。基于少数分类单元、单个分子标记或使用基于密码子的方法测试达尔文选择阳性的论文，但在缺乏实验证据的情况下，即所谓的选择氨基酸变化导致适应性表型效应，将不被接受。

影响因子趋势图