Abstract: The present teachings provide for identification of peptides using small sequence tags to focus computational resources on searching regions of a protein database that are the most likely to yield correct identifications. They allow for the incorporation of modifications and in doing so focuses the search to peptides with a precursor mass match. Additionally, probability or relevance factors can be used to determine peptide hypotheses. Various embodiments are presented that search for peptides when a single precursor is selected or when multiple precursors are simultaneously fragmented.

Abstract: The scientist domain-centric user interface system may prompt the user to supply scientist-centric information expressed utilizing terminology of a scientific domain, such as biology or analytical chemistry. A translation system then generates control parameters to control the search algorithm, thus relieving the user from having to learn how select and configure the algorithm control parameters directly.

Abstract: The present teachings provide methods and systems for the identification of proteins via peptide analysis. Some embodiments analyze proteins identified by analysis techniques such as mass spectrometry and build protein groups out of results. Groups can be formed by collecting like proteins and examining the group so as to identify if it is likely that only one form of a protein is present or, if there is enough evidence to support the presence of alternate forms. Various embodiments provide visual reports that can be interactive. These reports can allow a user to visualize relationships between proteins both intra- and inter-group. Methods are also introduced that can reduce the identification of false positives by taking into account a priori information.

Abstract: The scientist domain-centric user interface system may prompt the user to supply scientist-centric information expressed utilizing terminology of a scientific domain, such as biology or analytical chemistry. A translation system then generates control parameters to control the search algorithm, thus relieving the user from having to learn how select and configure the algorithm control parameters directly.

Abstract: The scientist domain-centric user interface system may prompt the user to supply scientist-centric information expressed utilizing terminology of a scientific domain, such as biology or analytical chemistry. A translation system then generates control parameters to control the search algorithm, thus relieving the user from having to learn how select and configure the algorithm control parameters directly.