Searching the World-Wide-Web using nucleotide and peptide sequences

*Background:* No approaches have yet been developed to allow instant searching of the World-Wide-Web by just entering a string of sequence data. Though general search engines can be tuned to accept ‘processed’ queries, the burden of preparing such ‘search strings’ simply defeats the purpose of quickly locating highly relevant information. Unlike ‘sequence similarity’ searches that employ dedicated algorithms (like BLAST) to compare an input sequence from defined databases, a direct ‘sequence based’ search simply locates quick and relevant information about a blunt piece of nucleotide or peptide sequence. This approach is particularly invaluable to all biomedical researchers who would often like to enter a sequence and quickly locate any pertinent information before proceeding to carry out detailed sequence alignment. 

*Results:* Here, we describe the theory and implementation of a web-based front-end for a search engine, like Google, which accepts sequence fragments and interactively retrieves a collection of highly relevant links and documents, in real-time. e.g. flat files like patent records, privately hosted sequence documents and regular databases. 

*Conclusions:* The importance of this simple yet highly relevant tool will be evident when with a little bit of tweaking, the tool can be engineered to carry out searches on all kinds of hosted documents in the World-Wide-Web.

*Availability:* Instaseq is free web based service that can be accessed by visiting the following hyperlink on the WWW
http://instaseq.georgetown.edu 
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Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Online Network Optimization Problems

. We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with minimal changes, a low cost subgraph of some type in a dynamically changing network. 1 Introduction In the early 1920's Otakar Bor uvka was asked by the Electric Power Company of Western Moravia (EPCWM) to assist in EPCWM's electrification of southern Moravia by solving from a mathematical standpoint the question of how to construct the most economical electric power network [9]. In 1926 Bor uvka initiated the study of network optimization problems, by publishing an efficient algorithm for constructing a minimum spanning tree of a fixed network [9]. Certainly since the 1920's the underlying collection of sites that require electrification in southern Moravia has changed frequently as new sites ..

Online Weighted Matching

We introduce and study online versions of weighted matching problems in metric spaces. We present a simple 2k \Gamma 1 competitive algorithm for online minimum weighted bipartite matching where 2k is the number of nodes. We show that this competitiveness is optimal. For online maximum matching, we prove that the greedy algorithm achieves an optimal competitive factor of 3. In contrast, we prove that the greedy algorithm performs exponentially poorly for online minimum matching. Key words. online algorithm, matching, weighted matching, competitiveness AMS(MOS) subject classifications. 68P05, 68Q25, 68R10, 68R05 1 Introduction The assignment problem, finding a bipartite matching of minimum weight, is one of the archetypical problems in algorithmic graph theory and in combinatorial optimization [2, 10]. We introduce a natural online version of this problem, which we call online min-matching. Let G be a complete bipartite graph with one bipartition designated as the server vertices, an..

Fault-Tolerant Real-Time Scheduling

We use competitive analysis to study how to best use redundancy to achieve faulttolerance in online real-time scheduling. We show that the optimal way to use spatial redundancy depends on a complex interaction of the benefits, execution times, release times, and latest start times of the jobs. We give a randomized online algorithm whose competitive ratio is O(log \Phi log \Delta log 2 n log m log log m ) for transient faults. Here n is the number of jobs, m is the number of processors, \Phi is the ratio of maximum value density of a job to the minimum value density of a job, and \Delta the ratio of the longest possible execution time to the shortest possible execution time. We show that this bound is close to optimal by giving an \Omega\Gamma log \Delta\Phi loglog m ( logm log log m ) 2 ) lower bound on the competitive ratio of any randomized algorithm. In the case of permanent faults, there is a randomized online algorithm that has a competitive ratio of O(log \Phi log \Delt..

Randomized Algorithms for Real-time Scheduling with Fault-tolerance

We investigate randomized on-line algorithms for real-time scheduling, and establish bounds on the optimal competitive ratio as function of the importance ratio \Phi, and the ratio \Delta of longest job length to shortest job length. We show that the competitive ratio of every deterministic algorithm is\Omega\Gamma/29 (\Phi= log \Phi; \Delta= log \Delta)). In contrast, we give a \Theta(min(ln \Phi; ln \Delta)) bound on the optimal randomized competitive ratio. For the uniform value density case, we present a randomized on-line algorithm that is 2competitive, and show that no randomized on-line algorithm can be better than 3 2 - competitive. We also consider the effect of processor faults. We give a randomized on-line algorithm that tolerates any number of processor faults, and has a competitive ratio of O(log \Phi\Delta \Delta log m= log log m), where m is the number of processors. We show that no randomized on-line algorithm can have a lower competitive ratio. 1 Introduction 1.1 Pr..

Maximizing Job Completions Online

We consider the problem of maximizing the number of jobs completed by their deadline in an online single processor system where the jobs are preemptable and have release times. So in the standard three field scheduling notation, this is the online version of the problem 1 j r i ; pmtn j P (1 \Gamma U i ). We present a deterministic algorithm Lax, and show that for every instance I, it is the case that either Lax, or the well-known deterministic algorithm SRPT (Shortest Remaining Processing Time), is constant competitive on I. An immediate consequence of this result is a constant competitive randomized algorithm for this problem. It is known that no constant competitive deterministic algorithm exists for this problem. This is the first time that this phenomenon, the randomized competitive ratio is constant in spite of the fact that the deterministic competitive ratio is nonconstant, has been demonstrated to occur in a natural online problem. This result is also a first step toward det..