The present disclosure provides advantageous systems and methods for identifying molecular vulnerabilities in biological pathways and networks. The present disclosure generally involves conceptualizing a disease/disorder at the molecular level as a faulty physiological system, wherein one or more molecules in the complex intracellular signaling network are dysfunctional. This is accomplished by modeling a given physiological system as a digital logic circuit. More particularly, in exemplarily embodiments, binary logic equations are derived by analyzing the interactions between the input and output nodes of a target biological system. These equations are then used to produce a digital circuit representation for the system. Once a digital circuit representation is created, this circuit may advantageously be analyzed, using fault analysis techniques, in order to determine the vulnerability levels of the molecules of the targeted system.

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (TMAO). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 M or urine with a normal biologic range of between about 0-1000 M.

Techniques and systems are disclosed for enabling a simulation environment for experimental design. The interactions of a configuration of molecules inside a biological structure or system, such as a cell (e.g., a neuron) or virtual test tube, are modeled using message-based techniques to communicate between molecules proximal to one another in a virtual 3-D geometric space. Some techniques and systems allow distributed processing of the individual molecular interactions across a plurality of work nodes. Some techniques and systems allow the storage of detailed information about the current state of the simulation of the biological model for each discrete time slice. This enables the ability for a 4-D playback/review of any particular spatial or temporal focus area of the simulation.

The present invention concerns 3D-crystals of complexes of ribosomal S6 kinase (RSK) and mitogen- and stress-activated protein kinase (MSK) proteins and their ligands, as well as methods for crystallization, three-dimensional structure determination and structure assisted methods for identifying ligands of said proteins.

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (TMAO). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 M or urine with a normal biologic range of between about 0-1000 M.

Embodiments of the invention relate to a constructing a gene interaction network. Tools are provided to compute a gene relationship measure based upon cellular images, and to rank image collections having a similar morphology. The ranking is based upon capturing similarity within the ranked collection by modeling a three dimensional shape of a cellular image stack. The graph is constructed for related images stacks. Nodes in the graph represent genes, and edges drawn between the nodes represent corresponding image stacks in a commonly ranked list. Accordingly, the graphical representation mathematically and visually connects respective genes.

Embodiments of the invention relate to a constructing a gene interaction network. Tools are provided to compute a gene relationship measure based upon cellular images, and to rank image collections having a similar morphology. The ranking is based upon capturing similarity within the ranked collection by modeling a three dimensional shape of a cellular image stack. The graph is constructed for related images stacks. Nodes in the graph represent genes, and edges drawn between the nodes represent corresponding image stacks in a commonly ranked list. Accordingly, the graphical representation mathematically and visually connects respective genes.