6230675
ARCS: an aggregated related column scoring scheme for aligned sequences
MOTIVATION
Biologists frequently align multiple biological sequences to determine consensus sequences and/or search for predominant residues and conserved regions. Particularly, determining conserved regions in an alignment is one of the most important activities. Since protein sequences are often several-hundred residues or longer, it is difficult to distinguish biologically important conserved regions (motifs or domains) from others. The widely used tools, Logos, Al2co, Confind, and the entropy-based method, often fail to highlight such regions. Thus a computational tool that can highlight biologically important regions accurately will be highly desired.


RESULTS
This paper presents a new scoring scheme ARCS (Aggregated Related Column Score) for aligned biological sequences. ARCS method considers not only the traditional character similarity measure but also column correlation. In an extensive experimental evaluation using 533 PROSITE patterns, ARCS is able to highlight the motif regions with up to 77.7% accuracy corresponding to the top three peaks.


AVAILABILITY
The source code is available on http://bio.informatics.indiana.edu/projects/arcs and http://goldengate.case.edu/projects/arcs
16784503
PhyloDraw: a phylogenetic tree drawing system
UNLABELLED
PhyloDraw is a unified viewing tool for phylogenetic trees. PhyloDraw supports various kinds of multi-alignment formats (Dialign2, Clustal-W, Phylip format, NEXUS, MEGA, and pairwise distance matrix) and visualizes various kinds of tree diagrams, e.g. rectangular cladogram, slanted cladogram, phylogram, unrooted tree, and radial tree. By using several control parameters, users can easily and interactively manipulate the shape of phylogenetic trees. This program can export the final tree layout to BMP (bitmap image format) and PostScript.


AVAILABILITY
http://pearl.cs.pusan.ac.kr/phylodraw/


CONTACT
jhchoi@pearl.cs.pusan.ac.kr
16402463
Towards application/file-level characterization of block references: a case for fine-grained buffer management
Two contributions are made in this paper. First, we show that system level characterization of file block references is inadequate for maximizing buffer cache performance. We show that a finer-grained characterization approach is needed. Though application level characterization methods have been proposed, this is the first attempt, to the best of our knowledge, to consider file level characterizations. We propose an Application/File-level Characterization (AFC) scheme where we detect on-line the reference characteristics at the application level and then at the file level, if necessary. The results of this characterization are used to employ appropriate replacement policies in the buffer cache to maximize performance. The second contribution is in proposing an efficient and fair buffer allocation scheme. Application or file level resource management is infeasible unless there exists an allocation scheme that is efficient and fair. We propose the ΔHIT allocation scheme that takes away a block from the application/file where the removal results in the smallest reduction in the number of expected buffer cache hits. Both the AFC and ΔHIT schemes are on-line schemes that detect and allocate as applications execute. Experiments using trace-driven simulations show that substantial performance improvements can be made. For single application executions the hit ratio increased an average of 13 percentage points compared to the LRU policy, with a maximum increase of 59 percentage points, while for multiple application executions, the increase is an average of 12 percentage points, with a maximum of 32 percentage points for the workloads considered.
9363851
Design, Implementation, and Performance Evaluation of a Detection-Based Adaptive Block Replacement Scheme
A new buffer replacement scheme, called DEAR (detection-based adaptive replacement), is presented for effective caching of disk blocks in the operating system. The proposed DEAR scheme automatically detects block reference patterns of applications and applies different replacement policies to different applications depending on the detected reference pattern. The detection is made by a periodic process and is based on the relationship between block attribute values, such as backward distance and frequency gathered in a period, and the forward distance observed in the next period. This paper also describes an implementation and performance measurement of the DEAR scheme in FreeBSD. The results from performance measurements of several real applications show that, compared with the LRU scheme, the proposed scheme reduces the number of disk I/Os by up to 51 percent, and the response time by up to 35 percent in the case of single application executions. For multiple application executions, the results show that the proposed scheme reduces the number of disk I/Os by up to 20 percent and the overall response time by up to 18 percent.
13403233
Auditable Privacy: On Tamper-Evident Mix Networks
We introduce the notion of tamper-evidence for mix networks in order to defend against attacks aimed at covertly leaking secret information held by corrupted mix servers. This is achieved by letting observers (which need not be trusted) verify the absence of covert channels by means of techniques we introduce herein. Our tamper-evident mix network is a type of re-encryption mixnet in which a server proves that the permutation and re-encryption factors that it uses are correctly derived from a random seed to which the server is committed.
10945598
An efficient merging algorithm for recovery and garbage collection in incremental checkpointing
15197780
Interprocedural pointer alias analysis
We present practical approximation methods for computing and representing interprocedural aliases for a program written in a language that includes pointers, reference parameters, and recursion. We present the following contributions: (1) a framework for interprocedural pointer alias analysis that handles function pointers by constructing the program call graph while alias analysis is being performed; (2) a flow-sensitive interprocedural pointer alias analysis algorithm; (3) a flow-insensitive interprocedural pointer alias analysis algorithm; (4) a flow-insensitive interprocedural pointer alias analysis algorithm that incorporates kill information to improve precision; (5) empirical measurements of the efficiency and precision of the three interprocedural alias analysis algorithms.