MOTIVATION: Co-expression networks are a powerful gene expression analysis method to study how genes co-express together in clusters with functional coherence that usually resemble specific cell type behavior for the genes involved. They can be applied to bulk-tissue gene expression profiling and assign function, and usually cell type specificity, to a high percentage of the gene pool used to construct the network. One of the limitations of this method is that each gene is predicted to play a role in a specific set of coherent functions in a single cell type (i.e. at most we get a single for each gene). We present here GMSCA (Gene Multifunctionality Secondary Co-expression Analysis), a software tool that exploits the co-expression paradigm to increase the number of functions and cell types ascribed to a gene in bulk-tissue co-expression networks. RESULTS: We applied GMSCA to 27 co-expression networks derived from bulk-tissue gene expression profiling of a variety of brain tissues. Neurons and glial cells (microglia, astrocytes and oligodendrocytes) were considered the main cell types. Applying this approach, we increase the overall number of predicted triplets by 46.73%. Moreover, GMSCA predicts that the SNCA gene, traditionally associated to work mainly in neurons, also plays a relevant function in oligodendrocytes. AVAILABILITYAND IMPLEMENTATION: The tool is available at GitHub, https://github.com/drlaguna/GMSCA as open-source software. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

We study the problem of geographic multicast routing in a wireless sensor network. In particular, we are interested in geographic routing solutions with a very limited control overhead and overall bandwidth consumption. Existing geographic multicast routing protocols require nodes to periodically exchange beacon messages to gather information about the position of their neighbors. These beacons represent a waste of resources, specially in areas of the network with no active communications. Beacons also induce significant problems in real deployments such as interferences and collisions that cause inconsistencies in neighboring tables. In this paper we propose a new beacon-less geographic multicast routing protocol called BRUMA. Unlike previous solutions, BRUMA uses the propagation of data packets to opportunistically select next hops among those that are reachable from the sending node. This allows the protocol to overcome most of the issues of beacon-based solutions in real deployments. Our simulations show that BRUMA achieves a higher packet delivery ratio and a lower overall bandwidth consumption than GMR, which is the protocol performing best among existing geographic multicast solutions.

Abstract Recent studies have shown that it is of paramount importance to take into account the error‐prone nature of wireless links when designing routing protocols for wireless sensor networks (WSNs). We propose a new protocol called localized energy‐efficient multicast algorithm (LEMA). By using a function to locally estimate the energy due to retransmissions, LEMA is able to deal with the inherent errors of WSN. This allows LEMA to find energy‐efficient paths to multiple destinations. Our simulation results show that LEMA is able to outperform even well‐known centralized heuristics such as minimum incremental power (MIP) and shortest path tree (SPT) based on energy, while still achieving a high packet delivery ratio (PDR). Copyright © 2007 John Wiley & Sons, Ltd.

Geographic routing (GR) algorithms, require nodes to periodically transmit HELLO messages to allow neighbors know their positions (beaconing mechanism). To reduce the control overhead due to theses messages, beacon-less routing algorithms have recently been proposed. However, existing beacon-less algorithms have not considered realistic physical layers. Therefore, those algorithms can not work properly in realistic scenarios. In this paper we present a new beacon-less routing protocol called BOSS. Its design is based on the conclusions of our open-field experiments using Tmote-sky sensors. BOSS is adapted to error-prone networks and uses a new delay function to reduce collisions and duplicate messages produced during the phase of selecting the next forwarder. Through extensive simulations we compare BOSS with BLR and CBF and show that our scheme is able to achieve almost perfect packet delivery ratio (like BLR) while having a low bandwidth consumption (even lower than CBF).

In the last few years, the amount of work in the field of routing algorithms for WSN has increased significantly. The special characteristics of WSN make a challenge for researchers to design efficient routing protocols. Nevertheless, most of the work done left out of scope an inherent aspect to WSN such as the radio transmission errors. The well-known unit disk graph model has been widely used as a basis for several routing protocol. However as recent experimental research has revealed, real links behave completely different to that model. In this paper we evaluate the problems that arise when considering that messages can be lost and propose a new geographic routing protocol which takes into account the probability of error transmission to achieve a high delivery ratio while reducing the energy consumed to the minimum possible. We present the results of the extensive simulation made using our protocol and compare it against a centralised version and two others previous work. Our protocol, being totally distributed and using only local information, outperforms the previous work and achieves almost the same results as the centralised version

Most usage scenarios for ad hoc and sensor networks require some degree of one-to-many or many-to-many interactions. In particular, for the case of sensor networks there is a number of scenarios in which a node has to send the same data to multiple destinations. Given that sensor networks have very limited resources, multicasting is a very interesting approach to deliver the same data packet to multiple destinations while reducing the amount of bandwidth and power consumption. In this paper, we present LEMA (localized energy-efficient multicast algorithm), a new energy-efficient multicast routing protocol based on geographic routing. The protocol is localized, as long as nodes currently routing multicast data packets are only required to know the coordinates of the destinations (locally obtained from the data packet to route) and the positions of its next hops. The protocol uses a localized source routing scheme to reach next hops which, unlike traditional geographic routing schemes, allows for the use of neighbors not providing advance to reduce the overall energy consumption. Our simulation results show that for networks with enough density the protocol is able to outperform even well-known centralized heuristics such as minimum incremental power (MIP) as well as shortest path tree (SPT) based on energy. For low-density networks, the protocol is still competitive for most scenarios

We present geographic multicast routing (GMR), a new multicast routing protocol for wireless sensor networks. GMR manages to preserve the good properties of previous geographic unicast routing schemes while being able to efficiently deliver multicast data messages to multiple destinations. It is a fully-localized algorithm (only needs information provided by neighbors) and it does not require any type of flooding throughout the network. Each node propagating a multicast data message needs to select a subset of its neighbors as relay nodes towards destinations. GMR optimizes cost over progress ratio. The cost is equal to the number of selected neighbors, while progress is the overall reduction of the remaining distances to destinations. That is, the difference between distance from current node to destinations and distance from selected nodes to destinations. Such neighbor selection achieves a good trade-off between the cost of the multicast tree and the effectiveness of the data distribution. Our cost-aware neighbor selection is based on a greedy set merging scheme achieving a O(Dn min(D, n)3) computation time, where n is the number of neighbors of current node and D is the number of destinations. This is superior to the exponential computational complexity of an existing solution (PBM) which tests all possible subsets of neighbours, and to an alternative solution that we considered, tests all the set partitions of destinations. Delivery to all destinations is guaranteed by applying face routing when no neighbor provides advance toward certain destinations. Our simulation results show that GMR outperforms previous multicast routing schemes in terms of cost of the trees and computation time over a variety of networking scenarios. In addition, GMR does not depend on the use of any parameter, while the closest competing protocol has one parameter and remains inferior for all values of that parameter