Topic: Molecular Data Storage: System Implementations and Coding Approaches

Abstract:

I will introduce the topic of molecular storage (e.g., DNA- and polymer-based data storage) through a series of four lectures that cover both experimental system reviews and mathematical approaches for desigining constrained and error-control coding schemes. The subjects will be organized in four thrusts, each covered by one lecture:

1) Concepts from synthetic biology relevant for understanding the operational principles of molecular storage.

2) Practical implementations of write, read, rewrite and random access protocols in molecular storage.

3) Constrained and error-control coding approaches for sequence-based storage.

4) Constrained and error-control coding approaches for topological and other storage approaches;

In the first lecture, I will discuss DNA and polymer synthesis, DNA sequencing, PCR protocols and DNA editing. In particular, the focus will be on microarray-based and solid state synthesis, as well as Sanger, nanopore and PacBio sequening techniques. The review will not require any specialized knowledge from the audience.

In the second lecture, I will review several DNA storage systems implementations, starting with the orginal design approaches from 2012, and continuing with DNA system designs that enable random access and nanopore-based data readouts. We will conclude the lecture with a review of topological and native storage and the concept of chemically modified DNA-based data storage.

In the third lecture, I will focus on describing constrained coding and error-control coding methods for various DNA storage channel models. The key ideas in this area are to enable unique and low-error-rate reconstruction of q-ary strings based on direct or indirect information about their substrings and subsequences, such as their composition, frequency, forbidden patterns etc. Concepts covered include de Bruijn and orthogonal de Bruijn strings, binary Bh codes, string reconstruction from substrings and weights of substrings, trace reconstruction and coded trace reconstruction.

During the fourth lecture, I will focus on coding methods for molecular storage systems that do not use sequence content to store information, such as topological DNA data storage and DNA tails. Here, the exposition will center on permutation and rank modulation codes with stuck-at errors, and new machine learning approaches for performing nonuniform error-correction.

Bio:

Olgica Milenkovic is the Franklin W. Woeltge professor of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign (UIUC), and Research Professor at the Coordinated Science Laboratory. She obtained her MS degree in mathematics in 2001 and PhD in electrical engineering in 2002, both from the University of Michigan, Ann Arbor.

Prof. Milenkovic heads a group focused on addressing unique interdisciplinary research challenges spanning the areas of algorithm design and computing, bioinformatics, coding theory, machine learning and signal processing. Her scholarly contributions have been recognized by multiple awards, including the NSF Faculty Early Career Development (CAREER) Award, the DARPA Young Faculty Award, the Dean’s Excellence in Research Award, the University of Michigan ECE Distinguished Educator Award and several best paper awards. In 2013, she became a UIUC Center for Advanced Study Associate and Willett Scholar while in 2015 she served as Distinguished Lecturer of the Information Theory Society. In 2018 she became an IEEE Fellow.

Prof Milenkovic has also served as Associate Editor of the IEEE Transactions on Communications, the IEEE Transactions on Signal Processing, the IEEE Transactions on Information Theory, the IEEE Transactions on Molecular, Biological and Multi-Scale Communications and the Transactions on Machine Learning Research. In 2009 and 2020 she assumed the role of Guest Editor-in-Chief of the IEEE Transactions on Information Theory on Molecular Biology and Neuroscience and the Memorial Tribute to V. I. Levenshtein.