### Table 2 Results of the comparison of our novel algorithm with existing methods in the literature. Shown is the identification rate in %.

1992

Cited by 1

### Table 5: The dynamic programming matrix of novel algorithm with PAM-80 scoring matrix.

2004

Cited by 1

### TABLE II LEAKAGE REDUCTION BY APPLICATION OF NOVEL ALGORITHMS COMPARED TO NON-OPTIMIZED VERSIONS IN %

### Table 5. Some representative novel PTMs identified by our algorithm. Spectra

in AN ACCURATE AND EFFICIENT ALGORITHM FOR PEPTIDE AND PTM IDENTIFICATION BY TANDEM MASS SPECTROMETRY

### Table 6.1: Performance of our hybrid hardware-accelerated algorithm for novel view synthesis of visual hulls.

2005

### Table 11. Sequencing results of Lutefisk, PepNovo, GST-SPC and our novel algorithm. The accurate subsequences are labeled in italics. M/Z means mass to charge ratio, Z means charge, and - means there is no result. M/

2007

"... In PAGE 11: ...............................................................................................................................................................61 Table11 . Sequencing results of Lutefisk, PepNovo, GST-SPC and our novel algorithm.... In PAGE 74: ... We think that better scoring function can help to improve the ratio of 100% match results. In Table11 , we have listed a few good interpretations of the novel algorithm, on which Lutefisk does not provide good results. It is interesting to note that more and longer peptide fragments are correctly sequenced by the novel algorithm - the power of preprocessing and the restricted anti-symmetric rule.... ..."

### Table 1: The test results of the effectiveness of the novel web text feature extraction algorithm.

2007

### Table 1. Performance of the novel algorithm - experimental analysis: Error-rate of the LFSR initial state reconstruction, as a function of the correlation noise p when the LFSR length is L = 40, the characteristic polynomial weight is 17, and the length of the sequence available for processing is N = 40000 bits.

2001

"... In PAGE 12: ... Note that the proposed algorithm can be applied for values of L signi cantly longer than L = 40, but this value was employed in all numerical and experimental illustrations for comparison with previously reported results. Results of the performance analysis are presented in Table1 . This table dis- plays the error-rate of the LFSR initial state reconstruction as a function of the correlation noise p when the algorithm employs: (i) OSDA with B = 18, 19, 20, 21, 22, (ii) IDA with N = 4096, B = 22, and at most 20 iterations.... ..."

Cited by 11

### Table 2. Comparison of the algorithms performance, assuming the same inputs, and lower complexity of the novel algorithm in comparison to the turbo algorithm [9]: Limit noise for which the algorithms yield, with probability close to 1, correct reconstruction of the initial LFSR state, when the LFSR characteristic polynomial is 1 + u + u3 + u5 + u9 + u11 + u12 + u17 + u19 + u21 + u25 + u27 + u29 + u32 + u33 + u38 + u40, and the available sample is 40000 bits.

2001

Cited by 11

### Table 2. Algorithms. Tools for genomic approaches to transcription control: Algorithms that can be used to identify potential regulatory sequences for known or novel transcription factors, to construct regulatory pathways or analyze microarrays.

"... In PAGE 12: ..., 2004). In Table2 I list algorithms and databases that may be helpful for identifying transcription factor binding sites within groups of genes. Figure 6.... ..."