activity
19972005
most citedA Solvable Sequence Evolution Model and Genomic Correlations

55 citations · 56 across the 4 of their papers we have counts for

collaborators

7 papers

q-bio.PE2005

Biodiversity in model ecosystems, II: Species assembly and food web structure

Ugo Bastolla, Michael Lässig, Susanna C. Manrubia +1

This is the second of two papers dedicated to the relationship between population models of competition and biodiversity. Here we consider species assembly models where the populat…

q-bio.PE2005

Biodiversity in model ecosystems, I: Coexistence conditions for competing species

Ugo Bastolla, Michael Lässig, Susanna C. Manrubia +1

This is the first of two papers where we discuss the limits imposed by competition to the biodiversity of species communities. In this first paper we study the coexistence of compe…

q-bio.GN200555 cited

A Solvable Sequence Evolution Model and Genomic Correlations

Philipp W. Messer, Peter F. Arndt, Michael Lässig

We study a minimal model for genome evolution whose elementary processes are single site mutation, duplication and deletion of sequence regions and insertion of random segments. Th…

cond-mat.stat-mech20021 cited

Structure and evolution of protein interaction networks: A statistical model for link dynamics and gene duplications

Johannes Berg, Michael Lässig, Andreas Wagner

The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure c…

nlin.AO2000

Diversity patterns from ecological models at dynamical equilibrium

U. Bastolla, M. Laessig, S. Manrubia +1

We study a dynamic model of ecosystems where immigration plays an essential role both in assembling the species community and in mantaining its biodiversity. This framework is part…

cond-mat1998

Optimizing Smith-Waterman alignments

Rolf Olsen, Terence Hwa, Michael Lassig

Mutual correlation between segments of DNA or protein sequences can be detected by Smith-Waterman local alignments. We present a statistical analysis of alignment of such sequences…