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The reconstruction of complete microbial metabolic pathways using ‘omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes. 

Emulating a shared atomic, read/write storage system is a fundamental problem in distributed computing. Replicating atomic objects among a set of data hosts was the norm for traditional implementations (e.g., [ 11]) in order to guarantee the availability and accessibility of the data despite host failures. As replication is highly storage demanding, recent approaches suggested the use of erasure-codes to offer the same fault-tolerance while optimizing storage usage at the hosts. Initial works focused on a fix set of data hosts. To guarantee longevity and scalability, a storage service should be able to dynamically mask hosts failures by allowing new hosts to join, and failed host to be removed without service interruptions. This work presents the first erasure-code based atomic algorithm, called ARES, which allows the set of hosts to be modified in the course of an execution. ARES is composed of three main components: (i) a reconfiguration protocol, (ii) a read/write protocol, and (iii) a set of data access primitives. The design of ARES is modular and is such to accommodate the usage of various erasure-code parameters on a per-configuration basis. We provide bounds on the latency of read/write operations, and analyze the storage and communication costs of the ARES algorithm. 

Shared register emulations on top of message- passing systems provide an illusion of a simpler shared memory system which can make the task of a system designer easier. Numerous shared register applications have a considerably high read to write ratio. Thus having algorithms that make reads more efficient than writes is a fair trade-off. Typically such algorithms for reads and writes are asymmetric and sacrifice the stringent consistency condition atomicity as it is impossible to have fast reads for multi-writer atomicity. Safety is a consistency condition has has gathered interest from both the systems and theory community as it is weaker than atomicity yet provides strong enough guarantees like “strong consistency” or read-my-write consistency. One requirement that is assumed by many researchers is that of the reliable broadcast (RB) primitive, which ensures the all or none property during a broadcast. One drawback is that such a primitive takes 1.5 rounds to complete. This paper implements an efficient multi-writer multi-reader safe register without using a reliable broadcast primitive. More- over, we provide fast reads or one-shot reads – our read operation can be completed in one round of client-to-server communication. Of course, this comes with the price of requiring more servers when compared to prior solutions assuming reliable broadcast. However, we show that this increased number of servers is indeed necessary as we prove a tight bound on the number of servers required to implement Byzantine-fault tolerant safe registers in a system without reliable broadcast. We extend our results to data stored using erasure coding as well. We present an emulation of single-writer multi-reader safe register based on MDS code. The usage of MDS code reduces storage cost and communication cost. On the negative side, we also show that to use MDS code and achieve one-shot read at the same time, we need even more servers.