Piriyapongsa et al. 8 present iLOCi, a new approach for detecting epistasis in genome-wide association studies, while Jensen et al. 9 have predicted bacterial growth from genomic sequences, using a Bayesian approach. Chen et al. 10 have carried out bacterial whole genome sequencing to identify pathogenicity-related genesm while Chu et al. 11 have developed MitoCounter to quantitaively report mitochondrial DNA copy numbers, important for aging dosorders. snpTree 12 is a new rapid standardised and automatic SNP analysis approach for epidemiological studies while 454 pyrosequencing, coupled with bioinformatics analysis, has been effectively used to sequence the dengue virus quasispecies 13.

Garg and Ranganathan 14 have developed a helminth secretome database from EST sequences, whereas Chen et al.15 present FastAnnotator for efficient transcript annotation. Menon et al. 16 have reported the large-scale annotation of the transcriptome of an economically important parasitic nematode. Vandenbon et al. 17 have systematically identified transcription factor pairs significantly co-occurring in a set of promoter sequences. Wu et al. 18 have uncovered novel multi-cancer differentially expressed gene candidates using meta-analytical biomarker search of EST expression data.

Khoo et al. 19 report the computational indentification and experimental validation of small RNAs (sRNAs) from Burkholderia pseudomallei, a soil bacterium which causes the disease melioidosis. Yang et al. 20 have proposed genetic buffering roles of for human microRNAs (miRNAs) on genome expression fluctuation. miRNAs can be used to design virus vaccines 21 while miRNAs and their targets can be rapidly identified even in plants 22. Lee et al. 23 have developed a comprehensive analytical approach for the functional annotation of miRNAs, while Chang et al. 24 have analyzed miRNAs in breast cancer.

Ali et al. 25 have developed organism-specific substitution matrices for improved protein annotation, while Grover et al. 26 report mechanistic insights into the anti-leishmanial activity of prospective herbal drugs. Chiu et al. 27 report pharmaceutical motifs for rapid identification of target proteins.

Kumar et al. 28 have engineered aggregation-prone recombinant proteins for substrate recognition by GroEL, while Wozniak et al. 29 have presented their results on finding drug resistance associated mutations in bacterial strains.

Praneenararat et al. 30 present NaviClusterCS for interactive and multi-scale network navigation in the big data era while Hsu and Yang 31 have uncovered pathway cross-talks based on functional relations between pathways. Hwang 32 has compared five methods of pathway-aggregation for gene expression data and report the best two. Li and Li 33 have identified disease genes by merging genotype and phenotype data using multigraph networks.

To leverage on the newly developed cloud computing technology, Chang et al. 34 have developed a de novo next-generation sequence assembler. An application of modern genome informatics to marine ecosystems is reported by Somboonna et al. 35, in their study of metagenomic profiles of free-living prokaryotes and eukaryotes in the coastal areas of Sichang Island in Thailand.

The best paper title was awarded to Li and Li for their advancement of disease gene identification using a new random walk model that allows cross-walking between phenotype and gene networks 33. The runners-up were Teo et al. 36 and Abbas et al. 37, in the BMC Bioinformatics supplement.