The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.</p

A Task-based Programming Methodology Using MCA Standards for Multicore Systems

Current trends in embedded platform design indicate that heterogeneous systems are here to stay. Thus, processors configured on the same platform may have different instruction-set architectures, different operating systems, and discrete memory space. These features increase the adaptability of the platforms for different applications. However, the development of such applications becomes difficult due to the system’s heterogeneity. Task parallelism is a classic approach to schedule work in parallel at the application level for symmetric or even asymmetric multicore processors (that may be heterogeneous in nature). A robust and efficient task-programming model to tackle parallelism for heterogeneous embedded systems is needed. In this thesis, we present a task-based programming model that deploys the Multicore Association’s (MCA) Task Management API, a robust, cross-platform and efficient API that targets both homogeneous and heterogeneous multicore systems. MTAPI provides an API to develop applications with task parallelism on multicore systems in a straightforward manner. The API supports different processor architectures and can be implemented on top of multiple operating systems or even bare metal. MTAPI can also work as a translation layer for higher-level programming models. We follow the MTAPI specification and design and implement an MTAPI Runtime Library (RTL). Our evaluation platforms are a multicore x86-64 computing node and an NVIDIA Jetson TK1 board with a CPU and a GPU on the same chip. We evaluate our MTAPI RTL implementation using applications from Rodinia and BOTS. We compare our MTAPI implementation with the Siemens MTAPI and with GCC-OpenMP, and observe that our MTAPI outperforms Siemens MTAPI significantly on the embedded board and competes favorably with GCC-OpenMP on both testbeds.Computer Science, Department o

Flowing Material Balance and Rate-Transient Analysis of Horizontal Wells in Under-Saturated Coal Seam Gas Reservoirs: A Case Study from the Qinshui Basin, China

Two phase flow and horizontal well completion pose additional challenges for rate-transient analysis (RTA) techniques in under-saturated coal seam gas (CSG) reservoirs. To better obtain reservoir parameters, a practical workflow for the two phase RTA technique is presented to extract reservoir information by the analysis of production data of a horizontal well in an under-saturated CSG reservoir. This workflow includes a flowing material balance (FMB) technique and an improved form of two phase (water + gas) RTA. At production stage of a horizontal well in under-saturated CSG reservoirs, a FMB technique was developed to extract original water in-place (OWIP) and horizontal permeability. This FMB technique involves the application of an appropriate productivity equation representing the relative position of the horizontal well in the drainage area. Then, two phase (water + gas) RTA of a horizontal well was also investigated by introducing the concept of the area of influence (AI), which enables the calculation of the water saturation during the transient formation linear flow. Finally, simulation and field examples are presented to validate and demonstrate the application of the proposed techniques. Simulation results indicate that the proposed FMB technique accurately predicts OWIP and coal permeability when an appropriate productivity equation is selected. The field application of the proposed methods is demonstrated by analysis of production data of a horizontal CSG well in the Qinshui Basin, China

The effects of cross-formational water flow on production in coal seam gas reservoir: a case study of Qinshui Basin in China

In coal seam gas (CSG) reservoirs, hydraulic connectivity usually exists between the coal and overlying permeable formation, which results in the delay of the dewatering process and a large volume of produced water. The cross-formational water flow can dramatically influence the production of CSG reservoirs, reduce the economic viability of production and increase the impact on the environment. To assess the cross-formational water flow of a CSG well, this study investigates the effects of cross-formational water flow from the overlying permeable formation on gas production. Simulation models are constructed to represent the water crossflow in four connection scenarios, including contact zone with and without penetrated fracture, and no-contact zone with and without penetrated fracture. The penetration ratio, defined as the ratio of fracture height in permeable formation to the formation thickness, is employed to characterize the extension degree of hydraulic fracture in the overlying formation. The effects of cross-formational water flow on CSG production are analyzed using dimensionless production curves and relative permeability curves calculated from the production history. The field application of this study is demonstrated by the production history of fractured CSG wells in the Qinshui Basin, China. The simulation results show that if the overlying formation is directly connected to the coal seam (contact zone scenario), the hydraulic fracture leads to the decrease of the peak gas production rate with the cumulative water production increasing dramatically. If the overlying formation is connected to the coal seam by hydraulic fractures only (no-contact zone scenario), gas production increases in two stages. Initially, the gas production rate exhibits a slow increase, followed by a fast increase before reaching the peak rate. When the hydraulic fracture penetrates the overlying formation, a 10% increase of the penetration ratio results in 0.55% and 1.82% increase of cumulative water production in the indirect and direct connection scenarios, respectively. In both scenarios, 10% penetration ratio increase leads to 7.41% reduction of gas production rate. The methods and simulation results presented in this work can be used to evaluate the impacts of cross-formational water flow on gas production and identify the cross-formational water flow in CSG wells from production history

An analytical model for pore volume compressibility of reservoir rock

The pore volume compressibility of reservoir rock is usually measured by volume method and the relation between compressibility and porosity follows the Hall plot. However, the volume method yields a high pore volume compressibility value and a negative correlation between compressibility and porosity. Both results illustrate that unconventional reservoirs with low porosity has higher elastic energy than conventional reservoirs with high porosity, which disagrees with the production practice.In this paper, volume method of pore volume compressibility is investigated and problems of Hall plot are analyzed. Then a novel analytical model on pore volume compressibility of reservoir rock is derived to resolve these problems. The reason on the improper results using volume method is discussed. The calculated results from our new model are validated by the experimental tests using mercury immersion method for pore volume compressibility measurement. The effects of compressibility on original oil in place and the flow radius are analyzed.The analytical model shows that pore volume compressibility of reservoir rock is related not only to porosity but also to elastic modulus and Poisson's ratio. There is a positive correlation between pore volume compressibility and porosity. The compressibility value of our model is much lower than that measured using volume method. The reason of the improper results from volume method is the micro interstice in core holder. Without the effects of micro interstice (mercury immersion method or loading and unloading stress treatment before the test), the measured pore volume compressibility shows a relatively low value and a positive correlation between pore compressibility and porosity, which validate the results of our analytical model. The pore volume compressibility calculated by volume method and Hall plot will overestimate the elastic energy of the reservoir and bring substantial errors in evaluation of original oil in place and the flow radius