Mangul Lab member Sei Chang reflects on summer undergraduate research experience

@article{mangul2019interpreting,
title = {Interpreting and integrating big data in the life sciences},
author = {Serghei Mangul},
url = {https://doi.org/10.1042/ETLS20180175},
doi = {10.1042/ETLS20180175},
year = {2019},
date = {2019-06-26},
journal = {Emerging Topics in Life Sciences},
volume = {3},
number = {4},
pages = {335-341},
publisher = {Portland Press Journals portal},
abstract = {Recent advances in omics technologies have led to the broad applicability of computational techniques across various domains of life science and medical research. These technologies provide an unprecedented opportunity to collect the omics data from hundreds of thousands of individuals and to study the gene–disease association without the aid of prior assumptions about the trait biology. Despite the many advantages of modern omics technologies, interpretations of big data produced by such technologies require advanced computational algorithms. I outline key challenges that biomedical researches are facing when interpreting and integrating big omics data. I discuss the reproducibility aspect of big data analysis in the life sciences and review current practices in reproducible research. Finally, I explain the skills that biomedical researchers need to acquire to independently analyze big omics data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{mangul2019bioinformatics,
title = {How bioinformatics and open data can boost basic science in countries and universities with limited resources},
author = {Serghei Mangul and Lana S Martin and Ben Langmead and Javier E Sanchez-Galan and Ian V Toma and Fereydoun Hormozdiari and Pavel Pevzner and Eleazar Eskin},
url = {https://doi.org/10.1038/s41587-019-0053-y},
doi = {10.1038/s41587-019-0053-y},
year = {2019},
date = {2019-03-04},
journal = {Nature Biotechnology},
volume = {37},
number = {3},
pages = {324},
publisher = {Nature Publishing Group},
abstract = {Providing training and access to standard computing hardware and cloud-based resources can enable scientists in lower-resource institutions and countries to reanalyze published ‘-omics’ data and produce career-enhancing STEM research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{mangul2018involving,
title = {Involving undergraduates in genomics research to narrow the education--research gap},
author = {Serghei Mangul and Lana S Martin and Eleazar Eskin},
url = {https://doi.org/10.1038/nbt.4113},
doi = {10.1038/nbt.4113},
year = {2018},
date = {2018-04-05},
journal = {Nature Biotechnology},
volume = {36},
number = {4},
pages = {369},
publisher = {Nature Publishing Group},
abstract = {Engaging undergraduates in computational tasks can improve genomic research laboratory productivity, benefiting both students and senior laboratory members.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{mangul2017addressing,
title = {Addressing the digital divide in contemporary biology: lessons from teaching UNIX},
author = {Serghei Mangul and Lana S Martin and Alexander Hoffmann and Matteo Pellegrini and Eleazar Eskin},
url = {https://doi.org/10.1016/j.tibtech.2017.06.007},
doi = {10.1016/j.tibtech.2017.06.007},
year = {2017},
date = {2017-07-15},
journal = {Trends in Biotechnology},
volume = {35},
number = {10},
pages = {901--903},
publisher = {Elsevier},
abstract = {Life and medical science researchers increasingly rely on applications that lack a graphical interface. Scientists who are not trained in computer science face an enormous challenge analyzing high-throughput data. We present a training model for use of command-line tools when the learner has little to no prior knowledge of UNIX.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}