Abstract: The invention provides for methods and compositions for treatment of pain via craniofacial mucosal administration of an analgesic compound (e.g. a non-opioid analgesic peptide, an NOP agonist or N/OFQ). Intranasal administration of certain analgesic peptides such as N/OFQ results in global analgesic effects.

Abstract: The disclosure provides compounds capable of selectively or non-selectively modulating nicotinic acetylcholine receptors. The compounds, compositions, and methods described herein are useful, for example, in treating patients suffering from various medical conditions including pain, chemical addictions, Parkinson's disease, Alzheimer's disease, and neurodegenerative disorders. In one embodiment, the compounds comprise a 7- to 11-membered azabicyclo ring.

Abstract: The invention provides for methods and compositions for treatment of pain via craniofacial mucosal administration of an analgesic compound (e.g. a non-opioid analgesic peptide, an NOP agonist or N/OFQ). Intranasal administration of certain analgesic peptides such as N/OFQ results in global analgesic effects.

Abstract: The invention provides for methods and compositions for treatment of pain via craniofacial mucosal administration of an analgesic compound (e.g. a non-opioid analgesic peptide, an NOP agonist or N/OFQ). Intranasal administration of certain analgesic peptides such as N/OFQ results in global analgesic effects.

Abstract: The disclosure provides compounds capable of selectively or non-selectively modulating nicotinic acetylcholine receptors. The compounds, compositions, and methods described herein are useful, for example, in treating patients suffering from various medical conditions including pain, chemical addictions, Parkinson's disease, Alzheimer's disease, and neurodegenerative disorders. In one embodiment, the compounds comprise a 7- to 11-membered azabicyclo ring.

Abstract: Disclosed are methods, software, and systems for comparing biopolymer sequences. The model includes at least two different characterizations of states of matching between segments of sequences at defined positions. Examples of states of matching include: similarity and dissimilarity between objects, as well as similarity to a reference, e.g., a reference sequence or a sequence profile. A topology of particular match states can be used to identify classes of sequences, e.g., preprohormone sequences.

Abstract: A model is used to represent a set of structured data objects that include elements at defined positions. The model includes distributions of vectors, each distribution corresponding to particular positions in the respective structured data objects, each of the vectors comprising values for the particular positions; and comparing a given set of structured data objects to the model to determine a likelihood that the given set is represented by the model. At least some of the distributions of the model differ such that different states of matching are indicated. Distributions of the model can indicate: dissimilarity between the structured data objects at defined positions; similarity between the structured data objects at defined positions; or similarity to a reference structure data object at defined positions.

Abstract: A model is used to represent a set of structured data objects that include elements at defined positions. The model includes distributions of vectors, each distribution corresponding to particular positions in the respective structured data objects, each of the vectors comprising values for the particular positions; and comparing a given set of structured data objects to the model to determine a likelihood that the given set is represented by the model. At least some of the distributions of the model differ such that different states of matching are indicated. Distributions of the model can indicate: dissimilarity between the structured data objects at defined positions; similarity between the structured data objects at defined positions; or similarity to a reference structure data object at defined positions.

Abstract: Disclosed are methods, software, and systems for comparing biopolymer sequences. The model includes at least two different characterizations of states of matching between segments of sequences at defined positions. Examples of states of matching include: similarity and dissimilarity between objects, as well as similarity to a reference, e.g., a reference sequence or a sequence profile. A topology of particular match states can be used to identify classes of sequences, e.g., preprohormone sequences.