Mile SIKIC

Mile SIKIC

Group Leader,
Laboratory of AI in Genomics

mile_sikic@gis.a-star.edu.sg

68088076

 

RESEARCH

Our research focuses on both computational biology and complex networks analysis.

A) Computational biology

We develop various algorithms on strings and graphs to improve and accelerate methods for mapping and de novo assembly of single genomes, metagenomes and transcriptomes. In addition we are particularly interested in genome phasing. We optimize our code utilizing SIMD (Single instruction multiple data) instructions on single core, and parallel programing on multi core and GPU architectures. In our work we use various machine learning, AI and signal processing methods to achieve maximal performance. We focus primarily, but not exclusively, on datasets produced using long read technologies developed by Oxford Nanopore Technologies (ONT) and Pacific Biosciences. The analysis of signal level information obtained from ONT sequences is of our particular interest. Using this information we plan to develop new methods for fast identification of microbes in metagenomics samples and modified nucleotides.


B) Complex network analysis

We focus our research on dynamics in complex networks. We study the question of inferring the source of a rumour or epidemic in a network. In addition we are interested in identifying exogenous and endogenous activity in social media. We investigate wisdom of the crowd approach to forecasting. We plan to use network for understanding microbial community dynamics at various scales and quantitative trait prediction from transcriptomic data.

Selected Publications

  • Šošic M, Šikic M "Edlib: a C/C ++ library for fast, exact sequence alignment using edit distance." Bioinformatics 2017 05 01 ; 33(9) : 1394-1395 Abstract
  • Vaser R, Sović I, Nagarajan N, Šikić M "Fast and accurate de novo genome assembly from long uncorrected reads." Genome Res 2017 05 ; 27(5) : 737-746 Abstract
  • Sović I*, Šikić M*, Wilm A, Fenlon SN, Chen S, Nagarajan N "Fast and sensitive mapping of nanopore sequencing reads with GraphMap." Nat Commun 2016 04 15 ; 7 : 11307 *These authors contributed equally Abstract
  • Vaser R, Adusumalli S, Leng SN, Sikic M, Ng PC "SIFT missense predictions for genomes." Nat Protoc 2016 01 ; 11(1) : 1-9 Abstract
  • Antulov-Fantulin N, Lančić A, Šmuc T, Štefančić H, Šikić M "Identification of Patient Zero in Static and Temporal Networks: Robustness and Limitations." Phys Rev Lett 2015 06 19 ; 114(24) : 248701 Abstract
  • Korpar M, Šikic M "SW#-GPU-enabled exact alignments on genome scale." Bioinformatics 2013 10 01 ; 29(19) : 2494-2495 Abstract
  • Sikić M1, Tomić S, Vlahovicek K "Prediction of protein-protein interaction sites in sequences and 3D structures by random forests." PLoS Comput Biol 2009 01 ; 5(1) : e1000278 Abstract