BACKGROUND: Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations. RESULTS: Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation. CONCLUSION: Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

BACKGROUND: Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations. RESULTS: We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms. CONCLUSIONS: The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/ . The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

This paper introduces CarSpeak, a communication system for autonomous driving. CarSpeak enables a car to query and access sensory information captured by other cars in a manner similar to how it accesses information from its local sensors. CarSpeak adopts a content-centric approach where information objects -- i.e., regions along the road -- are first class citizens. It names and accesses road regions using a multi-resolution system, which allows it to scale the amount of transmitted data with the available bandwidth. CarSpeak also changes the MAC protocol so that, instead of having nodes contend for the medium, contention is between road regions, and the medium share assigned to any region depends on the number of cars interested in that region.

We consider the problem of providing mobility support for Voice-over-IP (VoIP) traffic in small-scale enterprises. There is considerable interest in providing on-the-go support for VoIP through the use of WiFi-enabled smart phones. However, existing solutions either do not support client mobility or require client modifications, making them difficult to deploy in practice.

Given the abundance of cameras and LCDs in today's environment, there exists an untapped opportunity for using these devices for communication. Specifically, cameras can tune to nearby LCDs and use them for network access. The key feature of these LCD-camera links is that they are highly directional and hence enable a form of interference-free wireless communication. This makes them an attractive technology for dense, high contention scenarios. The main challenge however, to enable such LCD-camera links is to maximize coverage, that is to deliver multiple Mb/s over multi-meter distances, independent of the view angle. To do so, these links need to address unique types of channel distortions, such as perspective distortion and blur. This paper explores this novel communication medium and presents PixNet, a system for transmitting information over LCD-camera links. PixNet generalizes the popular OFDM transmission algorithms to address the unique characteristics of the LCD-camera link which include perspective distortion, blur, and sensitivity to ambient light. We have built a prototype of PixNet using off-the-shelf LCDs and cameras. An extensive evaluation shows that a single PixNet link delivers data rates of up to 12 Mb/s at a distance of 10 meters, and works with view angles as wide as 120 degree°.

Given the abundance of cameras and LCDs in today's environment, there exists an untapped opportunity for using these devices for communication. Specifically, cameras can tune to nearby LCDs and use them for network access. The key feature of these LCD-camera links is that they are highly directional and hence enable a form of interference-free wireless communication. This makes them an attractive technology for dense, high contention scenarios. The main challenge, however, to enable such LCD-camera links is to maximize coverage, that is to deliver multiple Mb/s over multi-meter distances, independent of the view angle. To do so, these links need to address unique types of channel distortions, such as perspective distortion and blur.

Enterprise WLANs have made a dramatic shift towards centralized architectures in the recent past. The reasons for such a change have been ease of management and better design of various control and security functions. The data path of WLANs, however, continues to use the distributed, random-access model, as defined by the popular DCF mechanism of the 802.11 standard. While theoretical results indicate that a centrally scheduled data path can achieve higher efficiency than its distributed counterpart, the likely complexity of such a solution has inhibited practical consideration. In this paper, we take a fresh, implementation and deployment oriented, view in understanding data path choices in enterprise WLANs. We perform extensive measurements to characterize the impact of various design choices, like scheduling granularity on the performance of a centralized scheduler, and identify regions where such a centralized scheduler can provide the best gains.Our detailed evaluation with scheduling prototypes deployed on two different wireless testbeds indicates that DCF is quite robust in many scenarios, but centralization can play a unique role in 1) mitigating hidden terminals - scenarios which may occur infrequently, but become pain points when they do and 2) exploiting exposed terminals - scenarios which occur more frequently, and limit the potential of successful concurrent transmissions. Motivated by these results, we design and implement CENTAUR - a hybrid data path for enterprise WLANs, that combines the simplicity and ease of DCF with a limited amount of centralized scheduling from a unique vantage point. Our mechanisms do not require client cooperation and can support legacy 802.11 clients.

Increased AP density in enterprise WLANs leads to increasing RF interference and decreasing performance. An important step towards mitigating this problem is to construct precise RF maps in the form of a conflict graph. Prior work on conflict graph construction, mostly using bandwidth tests [17], suffers from two problems: a) It is limited to static settings and cannot support mobility, and b) It incurs significant measurement overhead and must be performed offline (e.g. overnight). An alternative to bandwidth tests is "micro-probing" [4] that operates on millisecond-level time scales. Micro-probing rapidly constructs the conflict graph even while the network is in use (i.e. online). While interesting in principle, micro-probing has only been evaluated in simulation. In this work, we empirically study micro-probing on a 40-node wireless testbed. In doing so, we not only show that micro-probing is in fact practically realizable, but also present key insights that drive the design choices for our implementation. We benchmark micro-probing against bandwidth tests and find that micro-probing is just as accurate but with up to a 400 times reduction in overhead. Finally, we argue that a successful implementation of micro-probing opens up the space for further innovations in real-time WLAN adaptation and optimization.

Distributed repositories, containing digital documents are usually maintained and managed independently according to organization/users own requirements. Same information (i.e. documents containing same information) in different repositories, may be represented differently, makes it hard to retrieve desired information. Keyword based information retrieval technique helps in improving recall of user query result, but having low precision. To improve precision, we adopt semantic information retrieval technique. We are proposing architecture for semantic based information retrieval, in which plain text is read semantically and the extracted metadata is stored and later used for semantic search.

Wireless LANs are commonplace installations in enterprise environments. Their ease of use and deployment, however, are accompanied by a difficulty in their management and security. Proposed solutions to these problems are based on centralization; in the control plane through centralized authentication and allocation of channels and power levels, and in the data plane through time slotted medium access using centralized scheduling for interference mitigation. While centralization of some control plane tasks has been shown to be feasible, centralization on the data plane is significantly harder to realize. This is because it needs to take into account the inherent variability of the wireless medium while offering bounds on delay and jitter on the control paths. In this work, we present a study of the various problems that arise in centralization of the data plane in an enterprise WLAN. We believe that a pragmatic solution for data plane centralization is the key approachto provisioning an enterprise WLAN consisting of a dense deployment of APs.

Optimally choosing operating parameters for access points in an enterprise wireless LAN environment is a difficult and well-studied problem. Unlike past work, the SMARTA self-managing wireless LAN architecture dynamically adjusts both access point channel assignments and power levels in response to measured changes in the wireless environment to optimize arbitrary objective functions, while taking into account the irregular nature of RF propagation, and working with unmodified legacy clients. We evaluate the SMARTA architecture through simulation and show that our solution is not only feasible, but also provides significant improvements over existing approaches. For example, in a realistic scenario, SMARTA can provide 50% more throughput and 40% lower mean per-packet delay than a hand-optimized configuration. Moreover, SMARTA can automatically reconfigure channels and power levels in response to both small and large changes in the RF environment due to client movement.