Basic knowledge for a bioinformatician

Very often, esp. when I was interviewed for a job or talk with a knowledgable guy like Xiaopeng, I feel there are full of "holes" in the mass body of my knowledge. How awkward it is! Guess I am not the only one who feels the same.

As a senior-in-age-but-not-senior-in-knowledge bioinformatian, I would seriously recommend who will like to work in this field to have basic knowledge in the following subjects I can think of:
1. probability and statistics (not everyone know the difference between them)
2. machine learning (the 4-elements circle: data + algorithm + model + criteria)
3. programming design (knowing how to write script does not mean you know how to program; a good programer should learn the concept of how to write code in a inheritable manner).
4. algorithm and data structure (many know some algorithm, but to truly understand it is not a easy task. Binindex is a good example of using the concept of binary tree to store/query genomic coordinate in a super fast way.)
5. know how to appreciate a scientific work. (A paper can be good in way of (i) data sources (2) method and/or (3) idea. For sure it's also important to tell good paper from junk papers. I feel it's so important to enhance the sensitivity of 'smelling' a paper)

I found this nice reading list from Hendrik's page (http://www.liacs.nl/~hoogeboo/mcb/nature_primer.html)

How to apply de Bruijn graphs to genome assembly (Phillip E C Compeau, Pavel A Pevzner & Glenn Tesler) November 2011, Vol 29, No 11; pp 987 - 991 doi: 10.1038/nbt.2023 (?) Analyzing 'omics data using hierarchical models (Hongkai Ji & X Shirley Liu) April 2010, Vol 28, No 4; pp 337 - 340 doi: 10.1038/nbt.1619 (?) What is flux balance analysis? (Jeffrey D Orth, Ines Thiele & Bernhard Ø Palsson) March 2010, Vol 28, No 3; pp 245 - 248 doi: 10.1038/nbt.1614 (?) How does multiple testing correction work? (William S Noble) December 2009, Vol 27, No 12 ; pp 1135 - 1137 doi: 10.1038/nbt1209-1135 (?) How to visually interpret biological data using networks (Daniele Merico, David Gfeller & Gary D Bader) October 2009, Vol 27 No 10 ; pp 921 - 924 doi: 10.1038/nbt.1567 (?) How to map billions of short reads onto genomes (Cole Trapnell & Steven L Salzberg) May 2009, Vol 27, No 5; pp 455 - 457 doi: 10.1038/nbt0509-455 (?) SNP imputation in association studies (Eran Halperin & Dietrich A Stephan) April 2009, Vol 27, No 4; pp 349 - 351 doi: 10.1038/nbt0409-349 (?) Maximizing power in association studies (Eran Halperin & Dietrich A Stephan) March 2009, Vol 27, No 3; pp 255 - 256 doi: 10.1038/nbt0309-255 (?) Understanding genome browsing (Melissa S Cline & W James Kent) February 2009, Vol 27, No 2; pp 153 - 155 doi: 10.1038/nbt0209-153 (?) What are decision trees? (Carl Kingsford & Steven L Salzberg) September 2008, Volume 26, No 9; pp 1011 - 1013 doi: 10.1038/nbt0908-1011 (?) What is the expectation maximization algorithm? (Chuong B Do & Serafim Batzoglou) August 2008, Volume 26 No 8; pp 897 - 899 doi: 10.1038/nbt1406 (?) What is principal component analysis?  (Markus Ringnér) March 2008, Volume 26, No 3; pp 303 - 304 doi: 10.1038/nbt0308-303 (?) What are artificial neural networks? (Anders Krogh) February 2008, Volume 26, No 2; pp 195 - 197 doi: 10.1038/nbt1386 (?)

How does eukaryotic gene prediction work?  (Michael R Brent) August 2007, Volume 25, No 8; pp 883 - 885 doi: 10.1038/nbt0807-883 (?) How do shotgun proteomics algorithms identify proteins? (Edward M Marcotte) July 2007, Volume 25, No 7; pp 755 - 757 doi: 10.1038/nbt0707-755 (?) What is a support vector machine? (William S Noble) December 2006, Volume 24, No 12; pp 1565 - 1567 doi: 10.1038/nbt1206-1565 (?) How does DNA sequence motif discovery work? (Patrik D'haeseleer) August 2006, Volume 24, No 8; pp 959 - 961 doi: 10.1038/nbt0806-959 (?) What are DNA sequence motifs? (Patrik D'haeseleer) April 2006, Volume 24, No 4; pp 423 - 425 doi: 10.1038/nbt0406-423 (?) Inference in Bayesian networks (Chris J Needham, James R Bradford, Andrew J Bulpitt & David R Westhead) January 2006, Volume 24, No 1; pp 51 - 53 doi: 10.1038/nbt0106-51 (?) How does gene expression clustering work?  (Patrik D'haeseleer) December 2005, Volume 23, No 12; pp 1499 - 1501 doi: 10.1038/nbt1205-1499 (?) How do RNA folding algorithms work?  (Sean R Eddy) November 2004, Volume 22, No 11; pp 1457 - 1458 doi: 10.1038/nbt1104-1457 (?) What is a hidden Markov model?  (Sean R Eddy) October 2004, Volume 22, No 10; pp 1315 - 1316 doi: 10.1038/nbt1004-1315 (?) What is Bayesian statistics?  (Sean R Eddy) September 2004, Volume 22, No 9; pp 1177 - 1178 doi: 10.1038/nbt0904-1177 (?) Where did the BLOSUM62 alignment score matrix come from?  (Sean R Eddy) August 2004, Volume 22, No 8; pp 1035 - 1036 doi: 10.1038/nbt0804-1035 (?) What is dynamic programming?  (Sean R Eddy) July 2004, Volume 22, No 7; pp 909 - 910 doi: 10.1038/nbt0704-909 (?)

Getting Started in ... Getting Started in Gene Orthology and Functional Analysis (Fang G, Bhardwaj N, Robilotto R, Gerstein MB) PLoS Comput Biol (2010) 6(3): e1000703; doi: 10.1371/journal.pcbi.1000703 (?) Getting Started in Structural Phylogenomics (Sjölander K ) PLoS Comput Biol (2010) 6(1): e1000621 ; doi: 10.1371/journal.pcbi.1000621 (?) Getting Started in Gene Expression Microarray Analysis (Slonim DK, Yanai I) PLoS Comput Biol (2009) 5(10): e1000543; doi: 10.1371/journal.pcbi.1000543 (?) Getting Started in Text Mining: Part Two.  (Rzhetsky A, Seringhaus M, Gerstein MB) PLoS Comput Biol (2009) 5(7): e1000411. ; doi: 10.1371/journal.pcbi.1000411 (?) Getting Started in Computational Mass Spectrometry-Based Proteomics.  (Vitek O) PLoS Comput Biol (2009) 5(5): e1000366. ; doi: 10.1371/journal.pcbi.1000366 (?)

Getting Started in Computational Immunology. (Kleinstein SH ) PLoS Comput Biol (2008) 4(8): e1000128; doi: 10.1371/journal.pcbi.1000128 (?) Getting Started in Biological Pathway Construction and Analysis.  (Viswanathan GA, Seto J, Patil S, Nudelman G, Sealfon SC ) PLoS Comput Biol (2008) 4(2): e16; doi: 10.1371/journal.pcbi.0040016 (?) Getting Started in Text Mining (Cohen KB, Hunter L) PLoS Comput Biol (2008) 4(1): e20; doi: 10.1371/journal.pcbi.0040020 (?) Getting Started in Probabilistic Graphical Models.  (Airoldi EM ) PLoS Comput Biol (2007) 3(12): e252. ; doi: 10.1371/journal.pcbi.0030252 (?) Getting Started in Tiling Microarray Analysis (Liu XS) PLoS Comput Biol (2007) 3(10): e183; doi: 10.1371/journal.pcbi.0030183 (?) Ten Simple Rules Also the Ten Simple Rules series of editorials has a separate page at the PLoS journal. A link is now all you need to read about 'Ten Simple Rules for Getting Published' or '...for a Good Poster Presentation', etc. On the Process of Becoming a Great Scientist (Giddings MC) PLoS Comput Biol (2008) 4(2): e33; doi: 10.1371/journal.pcbi.0040033 (?)