2012年4月30日星期一

2012年4月27日星期五

current and historical climate data set for ecological modeling

https://www.climond.org/Default.aspx

Nexus data format and Newick tree format

1. Nexus data format for phylogenetic analysis
http://en.wikipedia.org/wiki/Nexus_file

2. Newick tree format for phylogenetic tree
http://en.wikipedia.org/wiki/Newick_format

implications for improving the quality of seeds - 系统进化研究的现实意义

These studies could have implications for improving the quality of seeds and, in turn, agricultural products ranging from food to clothing.

decipher evolutionary innovations - 解码进化创新

Having the architecture of this plant tree of life allows us to start to decipher some of the interesting aspects of evolutionary innovations that have occurred in this group.

noteworthy －值得注意的是

It is noteworthy that in this phylogenomic view of the seed plants, the basic topology of theangiosperm tree used by the Angiosperm Phylogeny Group (APG II, III) [35], [36] is supported with only minor changes (Figure S5).

essentially identical 本质上是相似的

The basic topologies for all three trees of the seed plants (MP-full, Figure S3; MP-30, Figure S4;and ML-30) are essentially identical.

some resources for NGS data analysis

http://vallandingham.me/

Bioinformatics

positive emotions and wellbeing - 好情绪与幸福

Positive emotions not only contribute to our success, they don't just contribute to our feeling good; they also contribute to our wellbeing.

积极情绪不仅有助成功，不仅能让我们感觉好，还有助我们获得幸福。

2012年4月26日星期四

python - some tutorials

1. free video on line
http://bimatics.blogspot.de/2009/06/python-programming-video-tutorials-for.html

2. http://www.dalkescientific.com/writings/NBN/

3. http://www.ics.uci.edu/~xhx/

4. http://www.awaretek.com/tutorials.html

checking the progress of plant whole genome sequencing - two sources

1. CoGePedia
http://genomevolution.org/wiki/index.php/Sequenced_plant_genomes

2. wiki pedia
http://en.wikipedia.org/wiki/List_of_sequenced_eukaryotic_genomes#Plants

2012年4月25日星期三

Julia - simple but robust, worthy of attention

http://julialang.org/

2012年4月24日星期二

2012年4月23日星期一

Plant genome diversity - a springer book

http://www.springerlink.com/content/978-3-7091-1129-1/contents/

Willis Lab - mimulus genomics

http://www.biology.duke.edu/willislab/

Wendel lab - cotton genomics

http://www.eeob.iastate.edu/faculty/WendelJ/home.htm

Evolutionary history of plant

1. http://en.wikipedia.org/wiki/Evolutionary_history_of_plants

2. http://tolweb.org/Green_plants

3. The plant tree of life: an overview and some points of view

the history of photosynthetic life on Earth

http://onlinelibrary.wiley.com/doi/10.1111/j.1365-313X.2011.04540.x/full

The Deep Roots of Eukaryotes

http://www.sciencemag.org/content/300/5626/1703.full

export R objects to MS word - an example

http://thebiobucket.blogspot.de/2012/04/reproducible-research-export-regression.html

2012年4月22日星期日

tuning your .rprofile

Customizing your .rprofile

Two incredibly useful functions to throw intoyour .rprofile

http://inundata.org/R_talks/meetup/

best scientific writing

http://mybiasedcoin.blogspot.de/2012/03/best-written-paper.html

How to Write Like a Scientist

http://sciencecareers.sciencemag.org/career_magazine/previous_issues/articles/2012_03_23/caredit.a1200033

Breaker lab - on RNAs and their functions

http://breaker.sites.yale.edu/Publications

2012年4月20日星期五

NESCent - right place to get funding for your independent evolutionary study

http://nescent.org/science/overview.php

nature careers - helpful guides for your career strategy

http://www.nature.com/nature/careers/index.html

tips on applying for postdoc position

http://cteg.berkeley.edu/~nielsen/2012/applying-for-postdocs-positions/

what makes or breaks a Phd student

http://bioinformatics.psb.ugent.be/jobs

Nature published a short career article about what makes or breaks a Phd student. We think the profile below matches our Phdstudents quite well. Does it match you?

Choose a supervisor whose work you admire and who is well supported by grants and departmental infrastructure.
Take responsibility for your project.
Work hard : long days all week and part of most weekends. If research is your passion this should be easy, and if it isn't,you are probably in the wrong field. Note who goes home with a full briefcase to work on at the end of the day. This is acause of success, not a consequence.
Take some weekends off, and decent holidays, so you don't burn out.
Read the literature in your immediate area, both current and past, and around it. You can't possibly make an original contribution to the literature unless you know what is already there.
Plan your days and weeks carefully to dovetail experiments so that you have a minimum amount of downtime.
Be creative : Think about what you are doing and why, and look for better ways to go. Don't see your PhD as just a road map laid out by your supervisor.
Develop good writing skills : they will make your scientific career immeasurably easier.
To be successful you must be at least four of the following: smart, motivated, creative, hard-working, skillful andlucky. You can't depend on luck, so you should better focus on the others!

We'd like to add one more thing to the list:

It's better to burn out than to fade away. Neil Young

the Bergelson lab - Arabidopsis thaliana

the Bergelson lab

2012年4月19日星期四

plant phylogeny - some articles

http://www.people.fas.harvard.edu/~ccdavis/publications.html

2012年4月18日星期三

data set from a re-sequencing project of rice

Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes

ftp://public.genomics.org.cn/BGI/rice/rice_resequencing/02.SNP/50_total/individual.txt

1 01 45975_AUS 45975_AUS C AUS
2 02 6307_AUS 6307_AUS C AUS
3 03 27762_IND 27762_IND C IND
4 04 30416_IND 30416_IND C IND
5 05 43545_IND 43545_IND C IND
6 06 51250_IND 51250_IND C IND
7 07 51300_IND 51300_IND C IND
8 08 8231_IND 8231_IND C IND
9 09 9148_IND 9148_IND C IND
10 10 9177_IND 9177_IND C IND
11 11 25901_IND 25901_IND C IND
12 12 6513_IND 6513_IND C IND
13 13 12883_AUS 12883_AUS C AUS
14 14 8555_AUS 8555_AUS C AUS
15 15 1107_TEJ 1107_TEJ C TEJ
16 16 27630_TEJ 27630_TEJ C TEJ
17 17 32399_TEJ 32399_TEJ C TEJ
18 18 2540_TEJ 2540_TEJ C TEJ
19 19 418_TEJ 418_TEJ C TEJ
20 20 55471_TEJ 55471_TEJ C TEJ
21 21 8191_TEJ 8191_TEJ C TEJ
22 22 NP_TEJ NP_TEJ C TEJ
23 23 11010_TRJ 11010_TRJ C TRJ
24 24 17757_TRJ 17757_TRJ C TRJ
25 25 328_TRJ 328_TRJ C TRJ
26 26 38698_TRJ 38698_TRJ C TRJ
27 27 43325_TRJ 43325_TRJ C TRJ
28 28 26872_TRJ 26872_TRJ C TRJ
29 29 43675_TRJ 43675_TRJ C TRJ
30 30 50448_TRJ 50448_TRJ C TRJ
31 31 66756_TRJ 66756_TRJ C TRJ
32 32 8244_TRJ 8244_TRJ C TRJ
33 33 12793_ARO 12793_ARO C ARO
34 34 38994_ARO 38994_ARO C ARO
35 35 9060_ARO 9060_ARO C ARO
36 36 9062_ARO 9062_ARO C ARO
37 37 RA4952_ARO RA4952_ARO C ARO
38 38 31856_ARO 31856_ARO C ARO
39 39 43397_TRJ 43397_TRJ C TRJ
40 40 60542_IV 60542_IV C IV
41 41 nivara_105327 N_105327 W N
42 42 nivara_106105 N_106105 W N
43 43 nivara_106154 N_106154 W N
44 44 nivara_80470 N_80470 W N
45 45 nivara_89215 N_89215 W N
46 46 rufipogon_105958 R_105958 W R
47 47 rufipogon_105960 R_105960 W R
48 48 rufipogon_Nepal R_Nepal W R
49 49 rufipogon_P46 R_P46 W R
50 50 rufipogon_YJ R_YJ W R

FastQC - a simple way to do some quality control checks on NGS data

http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.

The main functions of FastQC are

Import of data from BAM, SAM or FastQ files (any variant)
Providing a quick overview to tell you in which areas there may be problems
Summary graphs and tables to quickly assess your data
Export of results to an HTML based permanent report
Offline operation to allow automated generation of reports without running the interactive application

Cactus: Algorithms for genome multiple sequence alignment

PHAST and RPHAST - find conservative regions from genome alignment

PHAST and RPHAST: phylogenetic analysis with space/time models

http://compgen.bscb.cornell.edu/phast/comparison.php

http://compgen.bscb.cornell.edu/rphast/

enrichment for association between genomic regions and annotations

GREAT: Genomic Regions Enrichment of Annotations Tool

high level of creativity and depressed 创新与抑郁

If you want to have high level of creativity, it's a must you have to be depressed.

如果你想拥有高水平的创造力，就必须承受抑郁。

Analyzing Biological Data Using R: Methods for Graphs and Networks

http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-61779-361-5_19

R is a powerful language and widely used software tool for the analysis and visualization ofdata. Its core capabilities can be extended through many different add-on packages. Amongthe many packages are some which offer a broad range of facilities for analyzing statisticalproperties of graphs. This chapter provides a practical tutorial covering the use of R methodsfor graphs and networks to examine biological data and analyze their topological andstatistical properties.

Biological data analysis with R - a book

http://dyerlab.bio.vcu.edu/documents/

http://dyerlab.bio.vcu.edu/downloads/Dyer_Data_Analysis_Using_R.pdf

2012年4月17日星期二

perform evolutionary or population-based analyses directly on BAM/SAM files

POPBAM, http://popbam.sourceforge.net/

POPBAM is a tool to perform evolutionary or population-based analyses of next-generation sequencing data. POPBAM takes a BAM file as its input and can computemany widely used evolutionary genetics measures in sliding windows across agenome. The motivation for developing POPBAM is to provide the community with afundamental suite of evolutionary analyses tools that would otherwise be tedious toimplement. Since POPBAM works directly with BAM files, there are no intermediarysteps necessary.

To enable POPBAM to perform population-level analyses, it is first necessary to modify the input BAM file header. Users must add the "PO" tag to the header line for each read group. The "PO" tag can be any string, as long as the string is identical between samples from the same population. One example may be that a BAM file has three read groups (R21, R22, and R25). The R22 and R25 read groups are from two different lines of Drosophila melanogaster called "MEL01" and "MEL02", while the third read group, R21, is from a single line of D. simulans called "SIM01". Below is an example of the BAM header including the "PO" tag:

@RG  ID:R22  SM:MEL01  PO:MEL
@RG  ID:R25  SM:MEL02  PO:MEL
@RG  ID:R21  SM:SIM01  PO:SIM

2012年4月15日星期日

clark lab - population genetics

http://mbg.cornell.edu/cals/mbg/research/clark-lab/publications.cfm