Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: A method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A Software as a Service (SaaS) management platform (SMP) is provided, the SMP configured to perform a method including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A non-transitory computer-readable medium having program instructions for a method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A non-transitory computer-readable medium having program instructions for a method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A Software as a Service (SaaS) management platform (SMP) is provided, the SMP configured to perform a method including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A software as a service (SaaS) management platform, includes: an uploader process for receiving a plurality of contract files relating to purchases of a SaaS application; parsing logic that identifies terms in the plurality of contract files; normalization logic for assigning a normalization SKU to respective contract files based on the terms identified in the respective contract files; a background process that generates anonymized contract data by storing the terms of each contract file in association with the normalization SKU assigned to the contract file in an anonymous manner; a backend process that, responsive to a request from a client device, accesses the anonymized contract data to generate a distribution of terms of the anonymized contract data, generates benchmark data identifying an approximate location of terms of a given customer's contract file within the distribution, and returns the benchmark data to the client device for rendering through a user interface.

Abstract: A method implemented in a software as a service (SaaS) management platform, includes: receiving a plurality of contract files relating to purchases of a SaaS application; identifying terms in the plurality of contract files; assigning a normalization SKU to respective contract files based on the terms identified in the respective contract files; generating anonymized contract data by storing the terms of each contract file in association with the normalization SKU assigned to the contract file in an anonymous manner; responsive to a request from a client device, accessing the anonymized contract data to generate a distribution of terms of the anonymized contract data, generating benchmark data identifying an approximate location of terms of a given customer's contract file within the distribution, and returning the benchmark data to the client device for rendering through a user interface.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: Various methods and systems for performing analytics based on hierarchical categorization of content are provided. Analytics can be performed using an index building workflow and a classification workflow. In the index building workflow, documents are received and analyzed to extract features from the documents. Hierarchical category paths can be identified for the features. The documents are indexed to support searching the documents for the hierarchical category paths. In the classification workflow, a query, that includes or references content, may be received and analyzed to extract features from the content. The features are executed against a search engine that returns search result documents associated with hierarchical category paths. The hierarchical category paths from the search result documents may be used to generate a topic model of the content associated with the query.

Abstract: Search results are filtered using one or more rankers that evaluate a searcher intention to select items from a subset of search results. A subset of items may be provided that are responsive to a user search query. This subset of items may have one or more related properties and may be logically grouped together. A database of rankers may be evaluated and applied to the subset of items to determine items that are both relevant to the user search query and also correspond to a user intention for the search. As a result, the ranker may select and filter out certain items having one or more features that do not correspond to the user intention.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: The present disclosure generally relates to compositions and methods for improving the efficiency of homologous recombination. In particular, the disclosure relates to reagents and the use of such reagents.

Abstract: Various methods and systems for performing analytics based on hierarchical categorization of content are provided. Analytics can be performed using an index building workflow and a classification workflow. In the index building workflow, documents are received and analyzed to extract features from the documents. Hierarchical category paths can be identified for the features. The documents are indexed to support searching the documents for the hierarchical category paths. In the classification workflow, a query, that includes or references content, may be received and analyzed to extract features from the content. The features are executed against a search engine that returns search result documents associated with hierarchical category paths. The hierarchical category paths from the search result documents may be used to generate a topic model of the content associated with the query.

Abstract: Various methods and systems for performing analytics based on hierarchical categorization of content are provided. Analytics can be performed using an index building workflow and a classification workflow. In the index building workflow, documents are received and analyzed to extract features from the documents. Hierarchical category paths can be identified for the features. The documents are indexed to support searching the documents for the hierarchical category paths. In the classification workflow, a query, that includes or references content, may be received and analyzed to extract features from the content. The features are executed against a search engine that returns search result documents associated with hierarchical category paths. The hierarchical category paths from the search result documents may be used to generate a topic model of the content associated with the query.

Abstract: Modified E1a regulatory sequences are provided, wherein at least one Pea3 binding site, or a functional portion thereof, is deleted. Also provided are modified E1a sequences that selectively express particular isoforms. Also provided is an E1b-19K clone insertion site. These modified sequences can be used individually, or in combination with one another, to provide tumor-selective expression of proteins.

Abstract: The present disclosure generally relates to compositions and methods for improving the efficiency of homologous recombination. In particular, the disclosure relates to reagents and the use of such reagents.