Abstract. The Amorphous Computing project is aimed at developing programming methodologies for systems composed of vast numbers of locallyinteracting, identically-programmed agents. This paper presents some of the building blocks for robust collective behavior that have emerged as part of this effort, and describes how organizing principles from multi-cellular organisms may apply to multi-agent systems. 1

The method of microtubule tracking and dynamics analysis, presented here, improves upon the current means of manual and automated quantification of microtubule behavior. Key contributions are increasing accuracy and data volume, eliminating user bias and providing advanced analysis tools for the discovery of temporal patterns in cellular processes. By tracking the entire length of each resolvable microtubule, as opposed to only the tip, it is possible to boost dynamics studies with positional information that is virtually impossible to collect manually. We demonstrate the method on the analysis of a microtubule dataset, which was manually tracked and analyzed in the study of βIII-tubulin isoform. Our results show that automated recognition of temporal patterns in cellular processes offers a highly promising potential. 1.

Syntax Notation One (ASN.1), SGML, and the eXtensible Markup Language (XML) 23) . Among these languages, ASN.1 has been used as an alternative to the flat file in GenBank. ASN.1 is a powerful language for incorporating relational and object-oriented schemas directly in documents. However, ASN.1 requires strict definitions for all aspects of the schema. It is difficult to modify the structure of ASN.1 documents without adversely affecting the operation of tools that operate on them. Since relationships between biological entities are rapidly changing due to the progress of biotechnology,we focus on the ability to easily define, modify, and parse the structure and content of the document, rather than representation of strict inter-object relationships. In this case, XML seems a better candidate. An XML file (see Fig. 4) consists primarily of text data surrounded (marked up) by matching start and end tags. Provided the tags nest correctly (i.e, the regions they cover do not overlap), ...

Evolution of genetic code is studied as the change in the choice of enzymes that are used to synthesize amino acids from the genetic information of nucleic acids. We propose the following theory: the differentiation of physiological states of a cell allows for the different choice of enzymes, and this choice is later fixed genetically through evolution. To demonstrate this theory, a dynamical systems model consisting of the concentrations of metabolites, enzymes, amino acyl tRNA synthetase, and tRNA-amino acid complex in a cell is introduced and numerically studied. It is shown that the biochemical states of cells are differentiated by cell-cell interaction, and each differentiated type takes to use different synthetase. Through the mutation of genes, this difference in the genetic code is amplified and stabilized. Relevance of this theory to the evolution of non-universal genetic code in mitochondria is suggested. The present theory for the evolution of genetic code is based on our recent theory of isologous symbiotic speciation, which is briefly reviewed. According to the theory, phenotypes of organisms are first differentiated into distinct types through the interaction and developmental dynamics, even though they have identical genotypes, and later with the mutation in genotype, the genotype also differentiates into discrete types, while maintaining the ‘symbiotic ’ relationship between the types. Relevance of the theory to natural as well as artificial evolution is discussed. 1

iii First and foremost, I thank Prof. Niles Pierce. He has provided me with a working environment where I am free to explore topics that spark my curiosity, all the while participating in an ambitious research program making nucleic acids do things I never imagined they could. He is a good scientific citizen, committed to ethically and passionately conducting meaningful research, providing quality instruction in the classroom, reaching out to the youth in the community, and improving the Institute as a whole. In the last several years, he has profoundly influenced my development as a scientist, leading by example with skill, enthusiasm, and integrity. I have had the good fortune of being co-advised by (and being a teaching-assistant with) Prof. Zhen-Gang Wang. He has consistently provided clear, patient advice. His depth of understanding is apparent in his comments, and also in his probing questions. He has encouraged me to think deeply about scientific problems and to distill them to their essentials. He has very generously shared his talents with me, and I am very grateful. My other two committee members have also been very helpful to me in the past couple of years. Prof. Erik Winfree and his group are close collaborators, also being creative with nucleic acids. I have had many

The network of all pairwise protein physical interactions – the interactome – constitutes a key foundation for an integrated, post-genomic, study of an organism [1, 2, 3, 4, 5, 6]. Experimentally, the challenge lies in refining high-throughput capable techniques [7, 8, 9, 10] to generate more accurate and complete interactome data sets [11]. In parallel, a theoretical challenge is turning these large interaction data sets (e.g., rough estimates predict 40 000-200 000 interactions in human [12]) into meaningful maps – true guides to understanding and further exploring the biology of an organism [1, 5, 6]. Taking the yeast Saccharomyces cerevisiae interactome as a case study, we show here that, by combining two complementary theoretical network measures, betweenness centrality [13] and ‘Q-modularity ’ [14], a clearer picture of an interactome architecture is obtained. In particular, we show that the topology of the yeast interactome provides an ideal framework for the cell to physically implement the biological concept of coordinated yet distinct functional modules [15, 16, 17, 18]. Interestingly, this functional coordination

Abstract not found

Complete DNA sequences (genomes) and associated data are being made available worldwide at an astonishing rate. Through computer analysis of such data, molecular biologists hope to gain an overall understanding of the genome, such as by predicting large-scale gene networks. However, this is difficult because diverse genome data are scattered across many highly heterogeneous databases, and because existing database systems lack the facilities to expose and analyze functional relationships among the data. To address these problems, we propose a new type of genome database system. Since a genome can be thought of intuitively as a kind of ‘document’, our system uses a structured document language based on XML to effectively represent genomes and associated data. The information-rich structures of the genome documents help cope with data diversity and heterogeneity. A powerful query language is introduced that exposes important biological relationships among the genome data. We have obtained favorable results from several experiments, demonstrating the usefulness of our method in building a top-down view of genome functionality. 1

PACS. 05.40.-a – Fluctuation phenomena, random processes, noise, and Brownian motion.

Abstract. Mechanical oscillations are important for many cellular processes, e.g., the beating of cilia and flagella or the sensation of sound by hair cells. These dynamic states originate from spontaneous oscillations of molecular motors. A particularly clear example of such oscillations has been observed in muscle fibers under non-physiological conditions. In that case, motor oscillations lead to contraction waves along the fiber. By a macroscopic analysis of muscle fiber dynamics we find that the spontaneous waves involve non-hydrodynamic modes. A simple microscopic model of sarcomere dynamics highlights mechanical aspects of the motor dynamics and fits with the experimental observations. Spontaneous waves in muscle fibres 2 1.