BACKGROUND: Due to the ever-expanding gap between the number of proteins being discovered and their functional characterization, protein function inference remains a fundamental challenge in computational biology. Currently, known protein annotations are organized in human-curated ontologies, however, all possible protein functions may not be organized accurately. Meanwhile, recent advancements in natural language processing and machine learning have developed models which embed amino acid sequences as vectors in n-dimensional space. So far, these embeddings have primarily been used to classify protein sequences using manually constructed protein classification schemes. RESULTS: In this work, we describe the use of amino acid sequence embeddings as a systematic framework for studying protein ontologies. Using a sequence embedding, we show that the bacterial carbohydrate metabolism class within the SEED annotation system contains 48 clusters of embedded sequences despite this class containing 29 functional labels. Furthermore, by embedding Bacillus amino acid sequences with unknown functions, we show that these unknown sequences form clusters that are likely to have similar biological roles. CONCLUSIONS: This study demonstrates that amino acid sequence embeddings may be a powerful tool for developing more robust ontologies for annotating protein sequence data. In addition, embeddings may be beneficial for clustering protein sequences with unknown functions and selecting optimal candidate proteins to characterize experimentally.

No abstract available.

A key problem in operating systems is permitting the orderly introduction of new properties and new implementation techniques. We describe a mechanism, subcontract, that within the context of an object-oriented distributed system permits application programmers control over fundamental object mechanisms. This allows programmers to define new object communication mechanisms without modifying the base system. We describe how new subcontracts can be introduced as alternative communication mechanisms in the place of existing subcontracts. We also briefly describe some of the uses we have made of the subcontract mechanism to support caching, crash recovery, and replication.

This paper compares two working file servers in terms of their design goals, implementation issues, performance, and service experience. One server, the Xerox Distributed File System (XDFS) [10], was built at the Xerox Palo Alto Research Center; the other, the Cambridge File Server (CFS) [2, 3, 4], was built at the Cambridge University Computer Laboratory.

The cost of a change to a large software system is often primarily a function of the size of the system rather than the complexity of the change. One reason for this is that programs which access some given data structure must operate on it using notations which are determined by its exact representation. Thus, changing how it is implemented may necessitate changes to the programs which access it. This paper develops a programming language notation and semantic interpretations which allow a program to operate on a data object in a manner which is dependent only on its logical or abstract properties and independent of its underlying concrete representation.