The main strategy of algorithms in this class is to substitute “repeated strings”, i.e., exact replicas of a substring in a string, within the text with a convenient coding scheme. Those methods generally fall into the Macro Model for Data Compression introduced and studied by Storer and Szymanski (1982). The well known algorithms by Ziv and Lempel (1977, 1978), as well as many others, turn out...

Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life? Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us? Here I argue that a close examination of a particularly well-understood system--that of Escherichia coli chemotaxis--shows we are still a lon...

We propose a theoretical, yet realistic agent-based model and simulation platform of animal embryogenesis, called MecaGen, centered on the physico-chemical coupling of cell mechanics with gene expression and molecular signaling. This project aims to investigate the multiscale dynamics of the early stages of biological morphogenesis. Here, embryonic development is viewed as an emergent, self-org...

Understanding the structure, dynamics and function of proteins strongly parallels the mapping of words to meaning in natural language. Availability of large amounts of text in digital form has led to the convergence of linguistics with computational science, and has resulted in applications such as information retrieval and document summarization. In direct analogy, transformation of biology by...

S cientific research is an international endeavor, and computational biology is no exception. Last year we were fortunate enough to attend conferences and visit laboratories in a number of different countries and developing economies. Some of those countries had wellestablished programs in computational biology, while others had fledgling efforts in place and big plans. Because of its cost stru...

With the recent successful completion of the Human Genome Project and related attempts to determine whole genomes it has become obvious that the obtained wealth of data needs to be matched by information on the structure and function of the huge number of proteins encoded in the various genomes (“proteomics”). As proteins are only functional if they assume specific shapes, it is important to ex...

-Many aspects of biology (such as sequence information) are fundamentally digital in nature. This means that they are well suited to computational modeling and analysis. Prof. Manolis states that the genetic information must be digital, not analog because analog signals would be diluted from generation to generation. The information has to be digital to be minutely propagated throughout the cel...

Utilization of primary and secondary structure elements to predict a protein's propensity to form amyloids.

The complex biological systems consist of distinct molecules that exert their functions by interacting with each other, which makes it a big challenge to understand how the cellular machinery works. Recently, the accumulation of a large amount of multiscale omics data, such as nextgeneration sequencing data and protein interaction data, provides opportunity to investigate the functions of molec...

Deep learning is the trendiest tool in a computational biologist’s toolbox. This exciting class of methods, based on artificial neural networks, quickly became popular due to its competitive performance in prediction problems. In pioneering early work, applying simple network architectures to abundant data already provided gains over traditional counterparts in functional genomics, image analys...