background: rna plays key role in many aspects of biological processes and its tertiary structure is critical for its biological function. rna secondary structure represents various significant portions of rna tertiary structure. since the biological function of rna is concluded indirectly from its primary structure, it would be important to analyze the relations between the rna sequences and t...

background glucose is an essential element in the supply of body’s energy. in diseases such as diabetes, glucose increase is associated with disturbance in metabolism. cortisol is an important hormone in the regulation of glucose metabolism, and human serum albumin (hsa) is one of the most important glucose and cortisol transmitters in blood. interaction between albumin and these ligands could ...

dna sequence, containing all genetic traits is not a functional entity. instead, it transfers to protein sequences by transcription and translation processes. this protein sequence takes on a 3d structure later, which is a functional unit and can manage biological interactions using the information encoded in dna. every life process one can figure is undertaken by proteins with specific functio...

We consider the inverse-folding problem for RNA secondary structures: for a given (pseudo-knot-free) secondary structure we want to find a sequence that has a certain structure as its ground state. If such a sequence exists, the structure is called designable. We have implemented a branch-and-bound algorithm that is able to do an exhaustive search within the sequence space, i.e., gives an exact...

Understanding secondary structures of RNAs helps to determine their chemical and biological properties. Only a small number of RNA structures have been determined currently since such structure determination experiments are timeconsuming and expensive. As a result, scientists start to rely on RNA secondary structure prediction. Unlike protein structure prediction, predicting RNA secondary struc...

The thermodynamics of RNA secondary structure formation in small model systems provides a database for predicting RNA structure from sequence. Methods for making these measurements are reviewed with emphasis on optical methods and treatment of experimental errors. Analysis of experimental results in terms of simple nearest-neighbor models is presented. Some measured sequence dependences of non-...

The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.