A bioinformatics potpourri
BMC Genomics volume 19, Article number: 920 (2018)
The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26–28, 2018.
InCoB2017 was co-organized by The University of Technology Sydney, Tsinghua University, Graduate School at Shenzhen and APBioNet . Six keynote and two invited talks covered the latest bioinformatics applications and big data developments in basic and applied biomedical research. The theme of big data-driven bioinformatics and precision medicine was highlighted in a panel discussion on its current status and future. Jianzhu Chen (Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology) presented bioinformatics-driven immunological research towards the identification of transcription factors in memory CD8+ T cell development, and the screening of bioactive and natural compounds that are able to induce human macrophages into either inflammatory or anti-inflammatory states. Yuelong Shu of the School of Public Health (Shenzhen) at Sun Yat-sen University and WHO Collaborating Center for Reference and Research on Influenza demonstrated how large-scale sequencing of human influenza virus in combination with antigenic surveillance of hemagglutinin using the computational platform PREDAC improved vaccine strain recommendations for China.
Single cell RNA sequencing can reveal small differences among cells which are important to know in understanding of cellular responses to signals and variations among one cell type. Yong Hou (BGI-Shenzhen) gave in his invited talk a comprehensive overview of single cell sequencing, its application in cancer research and potential to improve cancer diagnosis. Limsoon Wong (National University of Singapore) provided insight into reproducibility and coverage issues of mass spectrometry-based proteomics data, and introduced algorithms that produce more robust and biologically meaningful proteomic profiling results.
Two keynotes covered epigenetic modifications in embryonic stem cells from the perspectives of miRNA regulation and networks of chromatin-related proteins. Xiujie Wang (Institute of Genetics and Developmental Biology, Chinese Academy of Sciences) reported on clusters of miRNAs that were positively correlated with the pluripotency level of embryonic stem cells. One of the miRNAs was involved in a new form of mRNA regulation through N6-methyladenosine modification. Alfonso Valencia (Barcelona Supercomputing Center) concentrated in his talk on network-based approaches in epigenomics, evolution and biomedicine on the role of 5-hydroxymethylcytosine as a communication hub in the chromatin network of embryonic stem cells, and concluded with a network property analysis that revealed inverse as well as direct co-morbidities between Alzheimer’s disease, glioblastoma and lung cancer.
Saman Halgamuge (The Australian National University) and Mindy Shi (University of North Carolina at Charlotte) offered in their presentations an impressive demonstration of deep learning applications. Saman Halgamuge showed in his keynote successful applications of unsupervised deep learning in the areas of direct drug-brain interactions, drug repositioning and multi-electrode array workflow applications for screening pharmacological compounds. Mindy Shi utilized deep learning to construct predictive models for quantitative trait locus network analysis using genomic and interactome data.
The Annual General Meeting of APBioNet on September 20th was opened with the President’s Report. Among the reporting items was a new simplified membership fee structure with details available at APBioNet website , and plans to utilize BioRxiv preprint server  and its feature to transfer manuscripts to partnering journals for article submissions related to InCoB or InSyB (International Symposium of Bioinformatics). The winner of the bid for InCoB2018, Shandar Ahmad, introduced next year’s conference venue at Jawaharlal Nehru University, New Delhi . Jim Hogan (Queensland University of Technology) presented an Expression of Interest (EOI) to host InCoB2019 or InCoB2020 at Gold Coast, Australia. Parties interested in hosting InCoB or InSyB as stand-alone, joint or back-to-back events are encouraged to submit an EOI through APBioNet’s website .
Manuscript submission and review
In total 152 manuscripts were submitted through EasyChair conference management system  for consideration for publication as InCoB2017 supplement articles in Bioinformatics, BMC Genomics, BMC Bioinformatics, BMC Systems Biology, BMC Medical Genomics, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Journal of Bioinformatics and Computational Biology (JBCB) or PeerJ. After peer review by at least two reviewers of the Program Committee comprising 121 members, supported by 27 external sub-reviewers (Additional file 1), 65 (42.7%) manuscripts were provisionally accepted in revised form before the conference, pending final editorial approval. Fifty-seven articles are published in InCoB2017 supplement issues of BMC Bioinformatics (22) BMC Medical Genomics (7), BMC Systems Biology (14) and BMC Genomics (14). Eight articles will appear in PeerJ (1), JBCB (3), TCBB (3) and Bioinformatics (1). Best Paper Awards in the categories Gold, Silver and Bronze were given to authors of 28 manuscripts (Additional file 2). The articles included in the four BMC supplement issues are briefly summarized in Table 1 according to 12 topic groups arranged in alphabetical order.
The potpourri of bioinformatics research output showcased at InCoB2017 reflects APBioNet’s goal to cater to a diverse range of practitioners and developers in the field. One of the highly cited articles of the InCoB conference series is an evaluation of human protein-protein interaction data in the public domain by Mathivanan et al.  with an average of ten citations per year. The paper was presented at InCoB2006 in New Delhi where next year’s conference will be held.
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Sharma A, Lopez Y, Tsunoda T. Divisive hierarchical maximum likelihood clustering. BMC Bioinformatics. 2017;18(Suppl 16):S12.
Sharma A, Kamola PJ, Tsunoda T. 2D-EM clustering approach for high-dimensional data through folding feature vectors. BMC Bioinformatics. 2017; 18 Suppl 16:S17.
White C, Ismail HD, Saigo H, Dukka BKC. CNN-BLPred: a convolutional neural network based predictor for β-lactamases (BL) and their classes. BMC Bioinformatics. 2017;18(Suppl 16):S19.
Xu Y, Zhou J, Zhou S, Guan J. CPredictor3.0: effectively detecting protein complexes from PPI networks with expression data and functional annotations. BMC Systems Biol. 2017;11(Suppl 7):S4.
Truong CD, Kwon Y-K. Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks. BMC Systems Biol. 2017;11(Suppl 7):S5.
Guo M, Wang C, Liu X, Wang S. Refine gene functional similarity network based on interaction networks. BMC Bioinformatics. 2017;18(Suppl 16):S16.
Mazaya M, Trinh H-C, Kwon Y-K. Construction and analysis of gene-gene dynamics influence networks based on a Boolean model. BMC Systems Biol. 2017;11(Suppl 7):S9.
Banos DT, Elati M, Trébulle P. Integrating transcriptional activity in genome-scale models of metabolism. BMC Systems Biol. 2017;11(Suppl 7):S7.
Zhang B-G, Li W, Shi Y, Liu X, Chen L. Detecting causality of short time-series data by prediction of topologically equivalent attractors. BMC Systems Biol. 2017;11(Suppl 7):S12.
Ma L, Jie ZJ. A polynomial based model for cell fate prediction in human diseases. BMC Systems Biol. 2017;11(Suppl 7):S2.
Li H, Venkatraman L, Narmada BC, White J, Yu H, Tucker-Kellogg L. Computational analysis reveals the coupling between bistability and the sign of a feedback loop in a TGF-β1 activation model. BMC Systems Biol. 2017;11(Suppl 7):S8.
Cai M, Li L. Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus. BMC Med Genet. 2017;18(Suppl 4):S6.
Hu W, Zhou X. Identification of prognostic signature in cancer based on DNA methylation interaction network. BMC Med Genet. 2017;18(Suppl 4):S7.
Dayton J, Piccolo S. Classifying cancer genome aberrations by their mutually exclusive effects on transcription. BMC Med Genet. 2017;10(Suppl 4):S3.
Jiang H, Ching W-K, Cheung W-S, Hou W, Yin H. Hadamard kernel SVM: applications for breast cancer outcome predictions. BMC Systems Biol. 2017;11(Suppl 7):S14.
Sun Y, Ma C, Halgamuge S. The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways. BMC Bioinformatics. 2017;18(Suppl 16):S5.
Taguchi Y-H. Tensor decomposition-based unsupervised feature extraction identifies candidate genes that induce post-traumatic stress disorder-mediated heart diseases. BMC Med Genet. 2017;10(Suppl 4):S2.
Shi J-Y, Huang H, Zhang Y-N, Long Y-X, Yiu S-M. Predicting binary, discrete and continued lncRNA-disease associations via a unified framework based on graph regression. BMC Med Genet. 2017;10(Suppl 4):S5.
Bao W-Z, Jiang Z-C, Huang D-S. Novel human microbe-disease association prediction using network consistency projection. BMC Bioinformatics. 2017;18(Suppl 16):S15.
Weifeng G, Shaowu Z, Qianqian S, Chengming Z, Tao Z, Luonan C. A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification. BMC Genomics. 2017;18(Suppl 11):S6.
Lee K, Lee M, Kim D. Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server. BMC Bioinformatics. 2017;18(Suppl 16):S7.
Asami S, Kiga D, Konagaya A. Constraint-based perturbation analysis with cluster Newton method : a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model. BMC Systems Biol. 2017;11(Suppl 7):S13.
Ji Z, Wang B, Yan K, Dong L, Meng G, Shi L. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy. BMC Systems Biol. 2017;11(Suppl 7):S1.
Pathak N, Lai M-L, Chen W-Y, Hsieh B-W, Yu G-Y, Yang J-M. Pharmacophore anchor models of flaviviral NS3 proteases lead to drug repurposing for DENV infection. BMC Bioinformatics. 2017;18(Suppl 16):S4.
Wang W, Yang X, Yang C, Guo XW, Zhang X, Wu C. Dependency-based long short term memory network for drug-drug interaction extraction. BMC Bioinformatics. 2017;18(Suppl 16):S9.
Osato N. Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes. BMC Genomics. 2017;18(Suppl S11):S13.
Chen K, Liu L, Zhang X, Yuan Y, Ren S, Guo J, Wang Q, Liao P, Li S, Cui X, Li Y-F, Zheng Y. Phased secondary small interfering RNAs in Panax notoginseng. BMC Genomics. 2017;18(Suppl 11):S5.
Liu Y-C, Chiu Y-J, Li J-R, Sun C-H, Liu C-C, Huang H-D. Biclustering of transcriptome sequencing data reveals human tissue-specific circular RNAs. BMC Genomics. 2017;18(Suppl 11):S9.
Liany H, Rajapakse J, Karuturi RKM. MultiDCoX: multi-factor analysis of differential co-expression. BMC Bioinformatics. 2017;18(Suppl 16):S10.
Wang X, Lin P, Ho JWK. Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest. BMC Genomics. 2017;18(Suppl 11):S14.
Kumar S, Sharma A, Tsunoda T. An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information. BMC Bioinformatics. 2017;18(Suppl 16):S11.
Khushi M, Dean I, Teber E, Chircop M, Arthur J, Flores-Rodriguez N. Automated classification and characterization of the mitotic spindle following knockdown of a mitosis-related protein. BMC Bioinformatics. 2017;18(Suppl 16):S13.
Zheng H, Wang R, Yu Z, Wang N, Gu Z, Zheng B. Automatic plankton image classification combining multiple view features via multiple kernel learning. BMC Bioinformatics. 2017;18(Suppl 16):S1.
Khan AM, Hu Y, Miotto O, Thevasagayam NM, Sukumaran R, HSA R, Brusic V, Tan TW, August JT. Analysis of viral diversity for vaccine target discovery. BMC Med Genet. 2017;10(Suppl 4):S1.
Lim WC, Khan AM. Mapping HLA-A2, A3 and B7 supertype-restricted T-cell epitopes in the ebolavirus proteome. BMC Genomics. 2017;18(Suppl 11):S2.
Pennisi M, Russo G, Ravalli S, Pappalardo F. Combining agent based-models and virtual screening techniques to predict the best citrus-derived vaccine adjuvants against human papilloma virus. BMC Bioinformatics. 2017;18(Suppl 16):S8.
Cao Y, Cao R, Huang Y, Zhou H, Liu Y, Li X, Zhong W, Hao P. A comprehensive study on cellular RNA editing activity in response to infections with different subtypes of influenza a viruses. BMC Genomics. 2017;18(Suppl 11):S4.
Cao Y, Huang Y, Xu K, Liu Y, Xu Y, Hao P, Zhong W, Li X. Differential responses of innate immunity triggered by different subtypes of influenza a viruses in human and avian hosts. BMC Med Genet. 2017;10(Suppl 4):S4.
Huang Y, Cao Y, Li J, Liu Y, Zhong W, Li X, Chen C, Hao P. A survey on cellular RNA editing activity in response to Candida albicans infections. BMC Genomics. 2017;18(Suppl 11):S3.
Miao J, Han N, Qiang Y, Zhang T, Li X, Zhang W. 16sPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing. BMC Bioinformatics. 2017;18(Suppl 16):S22.
Herath D, Tang S-L, Tandon K, Ackland D, Halgamuge S. CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision. BMC Bioinformatics. 2017;18(Suppl 16):S14.
Huang K-Y, Chang T-Z, Jhong J-H, Chi Y-H, Li W-C, Chan C-L, Lai KR, Lee T-Y. Identification of natural antimicrobial peptides from bacteria through metagenomic and metatranscriptomic analysis of high-throughput transcriptome data of Taiwanese oolong teas. BMC Systems Biol. 2017;11(Suppl 7):S3.
Wu Y-W. ezTree: an automated pipeline for identifying phylogenetic marker genes and inferring evolutionary relationships among uncultivated prokaryotic draft genomes. BMC Genomics. 2017;18(Suppl 11):S1.
Xing Y, Li G, Wang Z, Feng B, Song Z, Wu C. GTZ: a fast compression and cloud transmission tool optimized for FASTQ files. BMC Bioinformatics. 2017;18(Suppl 16):S20.
Low J, Khang TF, Tammi M. CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates. BMC Bioinformatics. 2017;18(Suppl 16):S21.
Wang Y, Li G, Ma M, He F, Song Z, Zhang W, Wu C. GT-WGS: an efficient and economic tool for large-scale WGS analyses based on the AWS cloud service. BMC Genomics. 2017;18(Suppl 11):S8.
Zhao Y, Sun C, Zhao D, Zhang Y, You Y, Jia X, Yang J, Wang L, Wang J, Fu H, Kang Y, Chen F, Jun Y, Wu J, Xiao J. PGAP-X: extension on pan-genome analysis pipeline. BMC Genomics. 2017;18(Suppl 11):S11.
Makita Y, Kawashima M, Lau NS, Matsui M, Othman AS. Construction of Pará rubber tree genome and multi-transcriptome database accelerates rubber researches. BMC Genomics. 2017;18(Suppl 11):S7.
Cheng L, Jiang Y, Ju H, Sun J, Zhou M, Hu Y, Peng J. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk. BMC Genomics. 2017;18(Suppl 11):S12.
Peng J, Wang H, Lu J, Hui W, Wang Y, Shang X. Identifying term relations cross different gene ontology categories. BMC Bioinformatics. 2017;18(Suppl 16):S6.
Liu Q, Wang J, Zhu Y, He Y. Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism. BMC Systems Biol. 2017;11(Suppl 7):S10.
Kao H-J, Weng S-L, Huang K-Y, Kaunang F-J, Hsu JB-K, Huang C-H, Lee T-Y. MDD-Carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs. BMC Systems Biol. 2017;11(Suppl 7):S11.
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Su M-G, Weng JT-Y, Hsu JB-K, Huang K-H, Chi Y-H, Lee TY. Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions. BMC Systems Biol. 2017;11(Suppl 7):S6.
Hardianto A, Yusuf M, Liu F, Ranganathan S. Exploration of charge states of balanol analogues acting as ATP-competitive inhibitors in kinases. BMC Bioinformatics. 2017;18(Suppl 16):S2.
Deng L, Fan C, Zeng Z. A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction. BMC Bioinformatics. 2017;18(Suppl 16):S18.
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We thank all reviewers and volunteering students and staff of Graduate School at Shenzen, Tsinghua University for their time and effort. We also thank Precision Medicine Research Center of Taihe Hospital (Hubei), School of Public Health (Shenzhen) at Sun Yat-sen University, School of Electrical and Information Engineering at Anhui University of Technology and International Society for Computational Biology for supporting InCoB2017.
The publication charge for this article was funded by APBioNet Ltd., Singapore. The funder had no role in the decision to publish or preparation of the manuscript.
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This article has been published as part of BMC Genomics Volume 19 Supplement 1, 2018: 16th International Conference on Bioinformatics (InCoB 2017): Genomics. The full contents of the supplement are available online at https://bmcgenomics.biomedcentral.com/articles/supplements/volume-19-supplement-1.
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CS, PH and MFS are elected office bearers of APBioNet. SR is a member of the Board of Directors of APBioNet Ltd., Singapore. All other authors have declared that no competing interests exist.
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Schönbach, C., Li, J., Ma, L. et al. A bioinformatics potpourri. BMC Genomics 19 (Suppl 1), 920 (2018). https://doi.org/10.1186/s12864-017-4326-x