Abstract: The present application is concerned with tricyclic pyrimidinones as inhibitors of WRN, as well as pharmaceutical compositions and methods of use related thereto. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: Disclosed are compounds of Formula (I), methods of using the compounds as immunomodulators, and pharmaceutical compositions comprising such compounds. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: The present application is concerned with bicyclic pyrimidinones as inhibitors of WRN, as well as pharmaceutical compositions and methods of use related thereto. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: Disclosed are compounds of Formula (I) and Formula (II), methods of using the compounds as immunomodulators, and pharmaceutical compositions comprising such compounds. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: Disclosed are compounds of Formula (I) and Formula (II), methods of using the compounds as immunomodulators, and pharmaceutical compositions comprising such compounds. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: Disclosed are compounds of Formula (I), methods of using the compounds as immunomodulators, and pharmaceutical compositions comprising such compounds. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: Disclosed are compounds of Formula (I), methods of using the compounds as immunomodulators, and pharmaceutical compositions comprising such compounds. The compounds are useful in treating, preventing, or ameliorating diseases or disorders such as cancer or infections.

Abstract: An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Abstract: An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Abstract: An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Abstract: An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Abstract: A system, computer-readable storage medium sorting at least one program, and a computer-implemented method for providing notifications to players of games are described. An identifier for a player of a first game is received. Notifications for at least one other game are obtained using the identifier for the player. The notifications for the at least one other game are transmitted to a device of the player, where the notifications for the at least one other game are to be displayed in a user interface for the first game.

Abstract: An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Abstract: Social network information of a player of a computer-implemented game is accessed to analyze a social interaction of the player with other players from the social network information to recommend other players of the social network of the player to further communicate with. A recommendation of other players is generated to the player based on a frequency of the social interaction. A selection of players from the recommendation is received from the player. A communication message is generated to the selected players.

Abstract: Social network information of a player of a computer-implemented game is accessed to identify active players from the social network information. The active players each have a minimum number of reciprocated communications with the player within a time range. A recommendation of players is generated to the player based on the identified active players.

Abstract: Social network information of a player of a computer-implemented game is accessed to identify non-active players from the social network information. The non-active players each have a minimum number of unreciprocated communications with the player within a time duration. A recommendation of the recommended players is generated to the player based on the non-active players.

Abstract: Systems and methods to provide game notifications are described. In some embodiments, a method receives an identifier for a player of a first multiplayer game and obtains multiple notifications using the identifier for the player. The multiple notifications are associated with at least one other multiplayer game. The method further determines a display order for displaying the plurality of notifications in a user interface for the first multiplayer game. The multiple notifications are transmitted to a device associated with the player in the display order and displayed in the user interface for the first multiplayer game in the display order.

Abstract: Social network information of a player of a computer-implemented game is accessed to identify active players from the social network information. The active players each have a minimum number of reciprocated communications with the player within a time range. A recommendation of players is generated to the player based on the identified active players.

Abstract: Social network information of a player of a computer-implemented game is accessed to identify non-active players from the social network information. The non-active players each have a minimum number of unreciprocated communications with the player within a time duration. A recommendation of the recommended players is generated to the player based on the non-active players.

Abstract: Social network information of a player of a computer-implemented game is accessed to analyze a social interaction of the player with other players from the social network information to recommend other players of the social network of the player to further communicate with. A recommendation of other players is generated to the player based on a frequency of the social interaction. A selection of players from the recommendation is received from the player. A communication message is generated to the selected players.