Cells seldom use any gene ‘‘as is,’’ but in connection with micro RNAs, manipulate their stored information so extensively and in such a context-sensitive way that it is cells, not genes, that seem to be the crucial agents in the biological process as a whole.
The mutual interactions among various developmental resources’’ reveal the genome to be not a set of instructions like a card-punched Jacquard loom, the model for the early computer programs from which the notion of ‘‘genetic program’’ got its inspiration, but rather part of a self-organizing developmental process that gives us at long last the answer to Waddington’s question about how organic form emerges and to Gould’s question about the origin of basic body plans. ‘‘The gene,’’ writes Keller, ‘‘is part and parcel of processes deﬁned and brought into existence by the action of a complex self-regulating dynamical system in which and for which the inherited DNA provides a crucial and absolutely indispensable raw material, but no more than that 1
From the year 2000 onwards, a new branch of biology, a concept called systems biology, has begun to be used widely in biology in a variety of contexts. The term systems biology was created by Bertalanffy in 1928. Systems biology focuses on complex interactions in biological systems by applying a holistic perspective. Altogether, this kind of thinking has led to the identification of ideas behind data processing in machines, such as silicon computers, but also created a bridge and inter-related approaches to the architecture and complex structuration of biological systems in nature. Cells and organisms work based on data flow. Data processing can be found in nature all down to the atomic and molecular level. Examples are DNA information storage and the histone code. Moreover, cells have the potential to compute ( process data), both intracellular (e.g. transcription networks) and during cell to cell communication. Higher-order cell systems such as the immune and the endocrine system, the homeostasis system, and the nerve system can be described as computational systems. The most powerful biological computer we know is the human brain.
Plato introduced in his dialogue Philebus a concept called System. A system is according to Plato a model for thinking about how complex structures are developed. Another idealistic philosopher, Kant, introduced, in 1790, in his Critique of Judgment the concept of self-organizing. Idealistic concepts based systemics have become important in contemporary science in order to understand complexity and big data problems. 9 Cybernetics explains complex systems that exist of a large number of interacting and interrelated parts.
It is a revolutionary paradigm shift in scientific thinking and has also major implications in regards to historical sciences, and the elucidation of origins of life, and biological diversity. Nature and computers are words that used to mean unrelated things. However, this view has changed with this scientific paradigm shift towards systems biology. One of the aims of systems biology is to model and discover properties of cells, tissues and organisms functioning as a system whose theoretical description is only possible using techniques of systems biology. These typically involve metabolic networks or cell signaling networks. As a field of study, particularly, the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system (for example, the enzymes and metabolites in a metabolic pathway or the heartbeats). Much effort has been made to elucidate the function of most of the biomolecular components and many of the interactions but that alone does not offer concepts or methods to understand how biological systems work holistically. The pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models. 8 Such inquiry can also give answers to how such systems could have emerged.
DNA is a blueprint to produce, amongst other things, proteins - molecular machines, which are discrete units, components of complex biological systems that are useful only in the completion of organismal subcomponents like organs, or organisms as a functional whole. The development gene regulatory network (dGRN) is like a central processing unit (CPU) the electronic circuitry within a computer that carries out the instructions of a computer program by performing the basic arithmetic, logic, controlling and input/output (I/O) operations specified by the instructions. It is like the control unit that orchestrates the fetching (from memory) and execution of instructions by directing the coordinated operations of the arithmetic logic unit (ALU).
In most—if not all—animals, the multicellular state is established in each generation through serial divisions of the zygote, where daughter cells produced by these divisions become an independent and fully specialized cell type. This functional specialization occurs largely during development and involves the tight coordination of cell proliferation, cell differentiation, tissue growth, and developmental genetic programs. Genes encoding transcription factors and signaling molecules are critical controllers of pattern formation and cell fate specification during development. Notably, most of these genes are highly conserved across animals (i.e., metazoans) and even their closest unicellular relatives. This striking level of conservation suggests that cell types and animal body plans are, at least partially, controlled by the regulatory capacities of these highly conserved genes. Yet, we cannot help but be intrigued by how such a conserved set of genes with few examples of gene expansions and little changes in their functionality can lead to the vast diversity of cell types and body plan forms found in animals. Transcription factors and signalling molecules participate in multiple, independent developmental processes.
Where Do Complex Organisms Come From?
To understand the major trends in animal diversity and if the various kinds of morphology are due to evolution, we must first understand how animal form is generated. As science has unravelled, the make of body form, phenotype, and organismal architecture is due to several genetic and principally, epigenetic interlocked and interconnected mechanisms. The modern, extended evolutionary synthesis does not take into consideration all relevant factors. Structuralism proposes that complex structure emerges holistically from the dynamic interaction of all parts of an organism. It denies that biological complexity can be reduced to natural selection, gene drift and gene flow, and argues that pattern formation is driven principally by multilevel processes that involve various functional units, working in an interdependent manner, pre-programmed to respond to ecological and environmental cues and conditions, food resource availability, and development programs. Various genetic and epigenetic Codes, an integrated understanding of the structural and functional aspects of epigenetics and several signalling pathways, nuclear architecture during differentiation, chromatin organisation, morphogenetic fields, amongst many other mechanisms.
The Gene regulation network
Chromatin dance in the nucleus through extensile motors
Post-transcriptional modifications (PTMs) of histones
The transcription factor Code
The DNA methylation code and language
Homeobox and Hox Genes
" Junk DNA "
Transposons and Retrotransposons
Signaling between cells orients the mitotic spindle
Ion Channels and Electromagnetic Fields
The Sugar Code