Multiple alignment of sequences is an important problem in bioinformatics. For example, multiple alignment of proteins belonging to the same family can provide valuable information for the common protein structure. Looking at a multiple alignment one can identify patterns which are not obvious if one looks at just pairwise alignments between members of the family. Traditional alignment schemes ...

We developed Græmlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (2) a parameter learning algorithm that uses a training set of known network alignments to learn parameters for our scoring function and thereby adap...

We developed Graemlin 2.0, a new multiple network aligner with (1) a new multi-stage approach to local network alignment; (2) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (3) a parameter learning algorithm that uses a training set of known network alignments t...

The process of aligning a group of protein sequences to obtain a meaningful Multiple Sequence Alignment (MSA) is a basic tool in current bioinformatic research. The development of new MSA algorithms raises the need for an efficient way to evaluate the quality of an alignment, in order to select the best alignment among the ones produced by the available algorithms. A natural way to evaluate the...

The technique of affine gaps allows calculations to perform alignment scoring without a strict linear score or gaps. Finding the best scoring alignment with this technique requires multiple arrays to be kept because the maximum score at any midpoint is not purely deterministic on the predecessors (which would require only one array) rather, multiple possible scores must be kept for each locatio...

On the domain of Choquet expected utility preferences with risk neutral lottery evaluation and totally monotone capacities, we demonstrate that proper scoring rules do not exist. This implies the non-existence of proper scoring rules for any larger class of preferences (CEU with convex capacities, multiple priors). We also show that if a decision maker whose behavior conforms to the multiple pr...

We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, find an alignment that minimizes the corresponding "sum of pairs" distance score. We generalize the divide-and-conquer technique described in [1,2], and present new ideas on how to use efficient search strategies for saving computer memory and accelerating the procedure ...

Œe BM25 ranking function is one of the most well known query relevance document scoring functions and many variations of it are proposed. Œe BM25F function is one of its adaptations designed formodeling documentswithmultiple fields. Œe Expanded Span method extends a BM25-like function by taking into considerations of the proximity between term occurrences. In this note, we combine these two var...

Protein sequence alignmentmay be viewed as either a classification or amultiple hypothesis testing problem.Whereas the type one error of a method is often studied for randomly generated sequences, the power is best investigated based on real protein sequences. The SCOP data base and its protein classification is used to investigate both the power and the type one error of sequence alignment as ...