Method for finding metabolic properties based on the general growth law. Liver examples. A General framework for biological modeling

We propose a method for finding metabolic parameters of cells, organs and whole organisms, which is based on the earlier discovered general growth law. Based on the obtained results and analysis of available biological models, we propose a general framework for modeling biological phenomena and discuss how it can be used in Virtual Liver Network project. The foundational idea of the study is that growth of cells, organs, systems and whole organisms, besides biomolecular machinery, is influenced by biophysical mechanisms acting at different scale levels. In particular, the general growth law uniquely defines distribution of nutritional resources between maintenance needs and biomass synthesis at each phase of growth and at each scale level. We exemplify the approach considering metabolic properties of growing human and dog livers and liver transplants. A procedure for verification of obtained results has been introduced too. We found that two examined dogs have high metabolic rates consuming about 0.62 and 1 gram of nutrients per cubic centimeter of liver per day, and verified this using the proposed verification procedure. We also evaluated consumption rate of nutrients in human livers, determining it to be about 0.088 gram of nutrients per cubic centimeter of liver per day for males, and about 0.098 for females. This noticeable difference can be explained by evolutionary development, which required females to have greater liver processing capacity to support pregnancy. We also found how much nutrients go to biomass synthesis and maintenance at each phase of liver and liver transplant growth. Obtained results demonstrate that the proposed approach can be used for finding metabolic characteristics of cells, organs, and whole organisms, which can further serve as important inputs for many applications in biology (protein expression), biotechnology (synthesis of substances), and medicine.Comment: 20 pages, 6 figures, 4 table

Replica Conditional Sequential Monte Carlo

We propose a Markov chain Monte Carlo (MCMC) scheme to perform state inference in non-linear non-Gaussian state-space models. Current state-of-the-art methods to address this problem rely on particle MCMC techniques and its variants, such as the iterated conditional Sequential Monte Carlo (cSMC) scheme, which uses a Sequential Monte Carlo (SMC) type proposal within MCMC. A deficiency of standard SMC proposals is that they only use observations up to time $t$ to propose states at time $t$ when an entire observation sequence is available. More sophisticated SMC based on lookahead techniques could be used but they can be difficult to put in practice. We propose here replica cSMC where we build SMC proposals for one replica using information from the entire observation sequence by conditioning on the states of the other replicas. This approach is easily parallelizable and we demonstrate its excellent empirical performance when compared to the standard iterated cSMC scheme at fixed computational complexity.Comment: To appear in Proceedings of ICML '1

Physical paradigm of Life as a generalization of biochemical conception. A Physical law governing life origin and development

The present view of biological phenomena is based on a biomolecular paradigm that development of living organisms is entirely defined by information stored in a molecular form as some genetic code. However, new facts and discoveries indicate that biological phenomena cannot be reduced to a biomolecular realm alone, but are also governed by mechanisms of other nature. These mechanisms, acting in tight cooperation with biochemical mechanisms, define life cycles of individual organisms, and, through this, the origin and evolution of the living world. Here, we present such a physical mechanism (General growth law), which represents a new physical law of nature acting at cellular, organ, system and whole organism levels, directing growth and reproduction together with biomolecular mechanisms. It imposes uniquely defined constraints on distribution of nutrients between biomass production and maintenance, thus defining the composition of biochemical reactions, their change and irreversibility during the organismal life cycle. Mathematically, this law is represented by the growth equation. Using this equation, we introduce growth models and explain division mechanisms for unicellular organisms. High adequacy of obtained results to experiments proves validity of the General growth law and of the new physical paradigm of Life based on this law.Comment: 38 pages, 8 figures, 1 table. Analysis of general principles of Life organization was added, as well as new material and two figures. In particular, analysis of views of E. Schrodinger, whose famous lectures contributed to origin of a biochemical paradigm, exposes what assumptions led him to make inaccurate conclusions. A new, more general physical paradigm of Life was propose